Combining LIANA and Tensor-cell2cell to decipher cell-cell communication across multiple samples.

Baghdassarian HM, Dimitrov D, Armingol E, Saez-Rodriguez J, Lewis NE.

Cell Rep Methods, 2024

doi:10.1016/j.crmeth.2024.100758.

Characterizing and targeting glioblastoma neuron-tumor networks with retrograde tracing

Tetzlaff SK, Reyhan E, Bengtson CP, Schroers J, Wagner J, Schubert MC, Layer N, Puschhof MC, Faymonville AJ, Drewa N, Pramatarov RL, Wissmann N, Alhalabi O, Heuer A, Sivapalan N, Campos J, Boztepe B, Scheck JG, Villa G, Schröter M, Sahm F, Forsberg-Nilsson K, Breckwoldt MO, Acuna C, Suchorska B, Heiland HD, Saez-Rodriguez J, Venkataramani V.

2024

doi:10.1101/2024.03.18.585565.

Learning tissue representation by identification of persistent local patterns in spatial omics data

Tanevski J, Vulliard L, Hartmann F, Saez-Rodriguez J.

2024

doi:10.1101/2024.03.06.583691.

Network integration of thermal proteome profiling with multi-omics data decodes PARP inhibition.

Burtscher ML, Gade S, Garrido-Rodriguez M, Rutkowska A, Werner T, Eberl HC, Petretich M, Knopf N, Zirngibl K, Grandi P, Bergamini G, Bantscheff M, Fälth-Savitski M, Saez-Rodriguez J.

Mol Syst Biol, 2024

doi:10.1038/s44320-024-00025-w.

Integrating single-cell multi-omics and prior biological knowledge for a functional characterization of the immune system.

Schäfer PSL, Dimitrov D, Villablanca EJ, Saez-Rodriguez J.

Nat Immunol, 2024

doi:10.1038/s41590-024-01768-2.

Metrics reloaded: recommendations for image analysis validation.

Maier-Hein L, Reinke A, Godau P, Tizabi MD, Buettner F, Christodoulou E, Glocker B, Isensee F, Kleesiek J, Kozubek M, Reyes M, Riegler MA, Wiesenfarth M, Kavur AE, Sudre CH, Baumgartner M, Eisenmann M, Heckmann-Nötzel D, Rädsch T, Acion L, Antonelli M, Arbel T, Bakas S, Benis A, Blaschko MB, Cardoso MJ, Cheplygina V, Cimini BA, Collins GS, Farahani K, Ferrer L, Galdran A, van Ginneken B, Haase R, Hashimoto DA, Hoffman MM, Huisman M, Jannin P, Kahn CE, Kainmueller D, Kainz B, Karargyris A, Karthikesalingam A, Kofler F, Kopp-Schneider A, Kreshuk A, Kurc T, Landman BA, Litjens G, Madani A, Maier-Hein K, Martel AL, Mattson P, Meijering E, Menze B, Moons KGM, Müller H, Nichyporuk B, Nickel F, Petersen J, Rajpoot N, Rieke N, Saez-Rodriguez J, Sánchez CI, Shetty S, van Smeden M, Summers RM, Taha AA, Tiulpin A, Tsaftaris SA, Van Calster B, Varoquaux G, Jäger PF.

Nat Methods, 2024

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Understanding metric-related pitfalls in image analysis validation.

Reinke A, Tizabi MD, Baumgartner M, Eisenmann M, Heckmann-Nötzel D, Kavur AE, Rädsch T, Sudre CH, Acion L, Antonelli M, Arbel T, Bakas S, Benis A, Buettner F, Cardoso MJ, Cheplygina V, Chen J, Christodoulou E, Cimini BA, Farahani K, Ferrer L, Galdran A, van Ginneken B, Glocker B, Godau P, Hashimoto DA, Hoffman MM, Huisman M, Isensee F, Jannin P, Kahn CE, Kainmueller D, Kainz B, Karargyris A, Kleesiek J, Kofler F, Kooi T, Kopp-Schneider A, Kozubek M, Kreshuk A, Kurc T, Landman BA, Litjens G, Madani A, Maier-Hein K, Martel AL, Meijering E, Menze B, Moons KGM, Müller H, Nichyporuk B, Nickel F, Petersen J, Rafelski SM, Rajpoot N, Reyes M, Riegler MA, Rieke N, Saez-Rodriguez J, Sánchez CI, Shetty S, Summers RM, Taha AA, Tiulpin A, Tsaftaris SA, Van Calster B, Varoquaux G, Yaniv ZR, Jäger PF, Maier-Hein L.

Nat Methods, 2024

doi:10.1038/s41592-023-02150-0.

Multiscale networks in multiple sclerosis.

Kennedy KE, Kerlero de Rosbo N, Uccelli A, Cellerino M, Ivaldi F, Contini P, De Palma R, Harbo HF, Berge T, Bos SD, Høgestøl EA, Brune-Ingebretsen S, de Rodez Benavent SA, Paul F, Brandt AU, Bäcker-Koduah P, Behrens J, Kuchling J, Asseyer S, Scheel M, Chien C, Zimmermann H, Motamedi S, Kauer-Bonin J, Saez-Rodriguez J, Rinas M, Alexopoulos LG, Andorra M, Llufriu S, Saiz A, Blanco Y, Martinez-Heras E, Solana E, Pulido-Valdeolivas I, Martinez-Lapiscina EH, Garcia-Ojalvo J, Villoslada P.

PLoS Comput Biol, 2024

doi:10.1371/journal.pcbi.1010980.

Complementing Cell Taxonomies with a Multicellular Analysis of Tissues.

Ramirez Flores RO, Schäfer PSL, Küchenhoff L, Saez-Rodriguez J.

Physiology (Bethesda), 2024

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Profiling the heterogeneity of colorectal cancer consensus molecular subtypes using spatial transcriptomics.

Valdeolivas A, Amberg B, Giroud N, Richardson M, Gálvez EJC, Badillo S, Julien-Laferrière A, Túrós D, Voith von Voithenberg L, Wells I, Pesti B, Lo AA, Yángüez E, Das Thakur M, Bscheider M, Sultan M, Kumpesa N, Jacobsen B, Bergauer T, Saez-Rodriguez J, Rottenberg S, Schwalie PC, Hahn K.

NPJ Precis Oncol, 2024

doi:10.1038/s41698-023-00488-4.

Compartments in medulloblastoma with extensive nodularity are connected through differentiation along the granular precursor lineage.

Ghasemi DR, Okonechnikov K, Rademacher A, Tirier S, Maass KK, Schumacher H, Joshi P, Gold MP, Sundheimer J, Statz B, Rifaioglu AS, Bauer K, Schumacher S, Bortolomeazzi M, Giangaspero F, Ernst KJ, Clifford SC, Saez-Rodriguez J, Jones DTW, Kawauchi D, Fraenkel E, Mallm JP, Rippe K, Korshunov A, Pfister SM, Pajtler KW.

Nat Commun, 2024

doi:10.1038/s41467-023-44117-x.

Metabolic Communication by SGLT2 Inhibition.

Billing AM, Kim YC, Gullaksen S, Schrage B, Raabe J, Hutzfeldt A, Demir F, Kovalenko E, Lassé M, Dugourd A, Fallegger R, Klampe B, Jaegers J, Li Q, Kravtsova O, Crespo-Masip M, Palermo A, Fenton RA, Hoxha E, Blankenberg S, Kirchhof P, Huber TB, Laugesen E, Zeller T, Chrysopoulou M, Saez-Rodriguez J, Magnussen C, Eschenhagen T, Staruschenko A, Siuzdak G, Poulsen PL, Schwab C, Cuello F, Vallon V, Rinschen MM.

Circulation, 2024

doi:10.1161/circulationaha.123.065517.

Collaborative effect of Csnk1a1 haploinsufficiency and mutant p53 in Myc induction can promote leukemic transformation.

Fuchs SNR, Stalmann USA, Snoeren IAM, Bindels E, Schmitz S, Banjanin B, Hoogenboezem RM, van Herk S, Saad M, Walter W, Haferlach T, Seillier L, Saez-Rodriguez J, Dugourd AJF, Lehmann KV, Ben-Neriah Y, Gleitz HFE, Schneider RK.

Blood Adv, 2024

doi:10.1182/bloodadvances.2022008926.

Predicting disease severity in multiple sclerosis using multimodal data and machine learning.

Andorra M, Freire A, Zubizarreta I, de Rosbo NK, Bos SD, Rinas M, Høgestøl EA, de Rodez Benavent SA, Berge T, Brune-Ingebretse S, Ivaldi F, Cellerino M, Pardini M, Vila G, Pulido-Valdeolivas I, Martinez-Lapiscina EH, Llufriu S, Saiz A, Blanco Y, Martinez-Heras E, Solana E, Bäcker-Koduah P, Behrens J, Kuchling J, Asseyer S, Scheel M, Chien C, Zimmermann H, Motamedi S, Kauer-Bonin J, Brandt A, Saez-Rodriguez J, Alexopoulos LG, Paul F, Harbo HF, Shams H, Oksenberg J, Uccelli A, Baeza-Yates R, Villoslada P.

J Neurol, 2024

doi:10.1007/s00415-023-12132-z.

A network-based transcriptomic landscape of HepG2 cells uncovering causal gene-cytotoxicity interactions underlying drug-induced liver injury.

Wijaya LS, Gabor A, Pot IE, van de Have L, Saez-Rodriguez J, Stevens JL, Le Dévédec SE, Callegaro G, van de Water B.

Toxicol Sci, 2024

doi:10.1093/toxsci/kfad121.

Drug-target identification in COVID-19 disease mechanisms using computational systems biology approaches.

Niarakis A, Ostaszewski M, Mazein A, Kuperstein I, Kutmon M, Gillespie ME, Funahashi A, Acencio ML, Hemedan A, Aichem M, Klein K, Czauderna T, Burtscher F, Yamada TG, Hiki Y, Hiroi NF, Hu F, Pham N, Ehrhart F, Willighagen EL, Valdeolivas A, Dugourd A, Messina F, Esteban-Medina M, Peña-Chilet M, Rian K, Soliman S, Aghamiri SS, Puniya BL, Naldi A, Helikar T, Singh V, Fernández MF, Bermudez V, Tsirvouli E, Montagud A, Noël V, Ponce-de-Leon M, Maier D, Bauch A, Gyori BM, Bachman JA, Luna A, Piñero J, Furlong LI, Balaur I, Rougny A, Jarosz Y, Overall RW, Phair R, Perfetto L, Matthews L, Rex DAB, Orlic-Milacic M, Gomez LCM, De Meulder B, Ravel JM, Jassal B, Satagopam V, Wu G, Golebiewski M, Gawron P, Calzone L, Beckmann JS, Evelo CT, D'Eustachio P, Schreiber F, Saez-Rodriguez J, Dopazo J, Kuiper M, Valencia A, Wolkenhauer O, Kitano H, Barillot E, Auffray C, Balling R, Schneider R, COVID-19 Disease Map Community.

Front Immunol, 2023

doi:10.3389/fimmu.2023.1282859.

MetalinksDB: a flexible and contextualizable resource of metabolite-protein interactions

Farr E, Dimitrov D, Turei D, Schmidt C, Lobentanzer S, Dugourd A, Saez-Rodriguez J.

2023

doi:10.1101/2023.12.30.573715.

A system-wide analysis of lipid transfer proteins delineates lipid mobility in human cells

Titeca K, Chiapparino A, Türei D, Zukowska J, van Ek L, Moqadam M, Triana S, Nielsen IØ, Foged MM, Gehin C, Maeda K, Alexandrov T, Saez-Rodriguez J, Reuter N, Hennrich ML, Gavin A.

2023

doi:10.1101/2023.12.21.572821.

Spatial transcriptomics of B cell and T cell receptors reveals lymphocyte clonal dynamics.

Engblom C, Thrane K, Lin Q, Andersson A, Toosi H, Chen X, Steiner E, Lu C, Mantovani G, Hagemann-Jensen M, Saarenpää S, Jangard M, Saez-Rodriguez J, Michaëlsson J, Hartman J, Lagergren J, Mold JE, Lundeberg J, Frisén J.

Science, 2023

doi:10.1126/science.adf8486.

A machine learning and directed network optimization approach to uncover <i>TP53</i> regulatory patterns.

Triantafyllidis CP, Barberis A, Hartley F, Cuervo AM, Gjerga E, Charlton P, van Bijsterveldt L, Rodriguez JS, Buffa FM.

iScience, 2023

doi:10.1016/j.isci.2023.108291.

Mapping cardiac remodeling in chronic kidney disease

Kaesler N, Cheng M, Nagai J, O’Sullivan J, Peisker F, Bindels E, Babler A, Moellmann J, Droste P, Franciosa G, Dugourd A, Saez-Rodriguez J, Neuss S, Lehrke M, Boor P, Goettsch C, Olsen J, Speer T, Lu T, Lim K, Floege J, Denby L, Costa I, Kramann R.

Sci Adv, 2023

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Mapping cardiac remodeling in chronic kidney disease.

Kaesler N, Cheng M, Nagai J, O'Sullivan J, Peisker F, Bindels EMJ, Babler A, Moellmann J, Droste P, Franciosa G, Dugourd A, Saez-Rodriguez J, Neuss S, Lehrke M, Boor P, Goettsch C, Olsen JV, Speer T, Lu TS, Lim K, Floege J, Denby L, Costa I, Kramann R.

Sci Adv, 2023

doi:10.1126/sciadv.adj4846.

Multicellular factor analysis of single-cell data for a tissue-centric understanding of disease.

Ramirez Flores RO, Lanzer JD, Dimitrov D, Velten B, Saez-Rodriguez J.

Elife, 2023

doi:10.7554/elife.93161.

A single-sample workflow for joint metabolomic and proteomic analysis of clinical specimens

Gegner HM, Naake T, Aljakouch K, Dugourd A, Kliewer G, Müller T, Schilling D, Schneider MA, Kunze-Rohrbach N, Grünewald TG, Hell R, Saez-Rodriguez J, Huber W, Poschet G, Krijgsveld J.

2023

doi:10.1101/2023.11.07.561857.

Expanding the coverage of regulons from high-confidence prior knowledge for accurate estimation of transcription factor activities.

Müller-Dott S, Tsirvouli E, Vazquez M, Ramirez Flores RO, Badia-I-Mompel P, Fallegger R, Türei D, Lægreid A, Saez-Rodriguez J.

Nucleic Acids Res, 2023

doi:10.1093/nar/gkad841.

Enablers and challenges of spatial omics, a melting pot of technologies.

Alexandrov T, Saez-Rodriguez J, Saka SK.

Mol Syst Biol, 2023

doi:10.15252/msb.202110571.

Microbiome-based risk prediction in incident heart failure: a community challenge

Erawijantari PP, Kartal E, Liñares-Blanco J, Laajala TD, Feldman LE, Carmona-Saez P, Shigdel R, Claesson MJ, Bertelsen RJ, Gomez-Cabrero D, Minot S, Albrecht J, Chung V, Inouye M, Jousilahti P, Schultz J, Friederich H, Knight R, Salomaa V, Niiranen T, Havulinna AS, Saez-Rodriguez J, Levinson RT, Lahti L, The FINRISK Microbiome DREAM Challenge and ML4Microbiome Communities.

2023

doi:10.1101/2023.10.12.23296829.

Assessing the impact of transcriptomics data analysis pipelines on downstream functional enrichment results

Paton V, Gabor A, Flores ROR, Badia-i-Mompel P, Tanevski J, Garrido-Rodriguez M, Saez-Rodriguez J.

2023

doi:10.1101/2023.09.13.557538.

Integration of Thermal Proteome Profiling with phosphoproteomic and transcriptomic data via mechanistic network models decodes the molecular response to PARP inhibition

Burtscher ML, Gade S, Garrido-Rodriguez M, Rutkowska A, Werner T, Eberl HC, Petretich M, Knopf N, Zirngibl K, Grandi P, Bergamini G, Bantscheff M, Fälth-Savitski M, Saez-Rodriguez J.

2023

doi:10.1101/2023.08.15.553354.

LIANA+: an all-in-one cell-cell communication framework

Dimitrov D, Schäfer PSL, Farr E, Rodriguez Mier P, Lobentanzer S, Dugourd A, Tanevski J, Ramirez Flores RO, Saez-Rodriguez J.

2023

doi:10.1101/2023.08.19.553863.

A network medicine approach to study comorbidities in heart failure with preserved ejection fraction.

Lanzer JD, Valdeolivas A, Pepin M, Hund H, Backs J, Frey N, Friederich HC, Schultz JH, Saez-Rodriguez J, Levinson RT.

BMC Med, 2023

doi:10.1186/s12916-023-02922-7.

Hepatocytes reprogram liver macrophages involving control of TGF-β activation, influencing liver regeneration and injury.

Wolf SD, Ehlting C, Müller-Dott S, Poschmann G, Petzsch P, Lautwein T, Wang S, Helm B, Schilling M, Saez-Rodriguez J, Vucur M, Stühler K, Köhrer K, Tacke F, Dooley S, Klingmüller U, Luedde T, Bode JG.

Hepatol Commun, 2023

doi:10.1097/hc9.0000000000000208.

Gene regulatory network inference in the era of single-cell multi-omics.

Badia-I-Mompel P, Wessels L, Müller-Dott S, Trimbour R, Ramirez Flores RO, Argelaguet R, Saez-Rodriguez J.

Nat Rev Genet, 2023

doi:10.1038/s41576-023-00618-5.

Proteomic Dynamics of Breast Cancer Cell Lines Identifies Potential Therapeutic Protein Targets.

Sun R, Ge W, Zhu Y, Sayad A, Luna A, Lyu M, Liang S, Tobalina L, Rajapakse VN, Yu C, Zhang H, Fang J, Wu F, Xie H, Saez-Rodriguez J, Ying H, Reinhold WC, Sander C, Pommier Y, Neel BG, Aebersold R, Guo T.

Mol Cell Proteomics, 2023

doi:10.1016/j.mcpro.2023.100602.

Democratizing knowledge representation with BioCypher.

Lobentanzer S, Aloy P, Baumbach J, Bohar B, Carey VJ, Charoentong P, Danhauser K, Doğan T, Dreo J, Dunham I, Farr E, Fernandez-Torras A, Gyori BM, Hartung M, Hoyt CT, Klein C, Korcsmaros T, Maier A, Mann M, Ochoa D, Pareja-Lorente E, Popp F, Preusse M, Probul N, Schwikowski B, Sen B, Strauss MT, Turei D, Ulusoy E, Waltemath D, Wodke JAH, Saez-Rodriguez J.

Nat Biotechnol, 2023

doi:10.1038/s41587-023-01848-y.

Single-cell biology: what does the future hold?

Polychronidou M, Hou J, Babu MM, Liberali P, Amit I, Deplancke B, Lahav G, Itzkovitz S, Mann M, Saez-Rodriguez J, Theis F, Eils R.

Mol Syst Biol, 2023

doi:10.15252/msb.202311799.

Spatially resolved multiomics on the neuronal effects induced by spaceflight

Masarapu Y, Cekanaviciute E, Andrusivova Z, Westholm JO, Björklund Å, Fallegger R, Badia-i-Mompel P, Boyko V, Vasisht S, Saravia-Butler A, Gebre S, Lázár E, Bergmann O, Taylor D, Wallace D, Sylvén C, Rodriguez JS, Galazka J, Costes S, Giacomello S.

2023

doi:10.21203/rs.3.rs-2865086/v1.

Single-cell transcriptomics reveal distinctive patterns of fibroblast activation in murine heart failure with preserved ejection fraction

Lanzer JD, Wienecke LM, Ramirez-Flores RO, Zylla MM, Hartmann N, Sicklinger F, Schultz J, Frey N, Saez-Rodriguez J, Leuschner F.

2023

doi:10.1101/2023.05.09.539983.

Combining LIANA and Tensor-cell2cell to decipher cell-cell communication across multiple samples

Baghdassarian H, Dimitrov D, Armingol E, Saez-Rodriguez J, Lewis NE.

2023

doi:10.1101/2023.04.28.538731.

Expanding the coverage of regulons from high-confidence prior knowledge for accurate estimation of transcription factor activities

Müller-Dott S, Tsirvouli E, Vázquez M, Ramirez Flores RO, Badia-i-Mompel P, Fallegger R, Lægreid A, Saez-Rodriguez J.

2023

doi:10.1101/2023.03.30.534849.

Best practices for single-cell analysis across modalities.

Heumos L, Schaar AC, Lance C, Litinetskaya A, Drost F, Zappia L, Lücken MD, Strobl DC, Henao J, Curion F, Single-cell Best Practices Consortium, Schiller HB, Theis FJ.

Nat Rev Genet, 2023

doi:10.1038/s41576-023-00586-w.

International Society of Nephrology first consensus guidance for preclinical animal studies in translational nephrology.

Nangaku M, Kitching AR, Boor P, Fornoni A, Floege J, Coates PT, Himmelfarb J, Lennon R, Anders HJ, Humphreys BD, Caskey FJ, Fogo AB, TRANSFORM group.

Kidney Int, 2023

doi:10.1016/j.kint.2023.03.007.

A T follicular helper cell origin for T regulatory type 1 cells.

Solé P, Yamanouchi J, Garnica J, Uddin MM, Clarke R, Moro J, Garabatos N, Thiessen S, Ortega M, Singha S, Mondal D, Fandos C, Saez-Rodriguez J, Yang Y, Serra P, Santamaria P.

Cell Mol Immunol, 2023

doi:10.1038/s41423-023-00989-z.

Multiscale networks in multiple sclerosis

Kennedy KE, Kerlero de Rosbo N, Uccelli A, Cellerino M, Ivaldi F, Contini P, De Palma R, Harbo HH, Berge T, Bos SD, Høgestøl EA, Brune-Ingebretsen S, de Rodez Benavent S, Paul F, Brandt AU, Bäcker-Koduah P, Behrens J, Kuchling J, Asseyer SE, Scheel M, Chien C, Zimmermann H, Motamedi S, Kauer-Bonin J, Saez-Rodriguez J, Rinas M, Alexopoulos L, Andorra M, Llufriu S, Saiz A, Blanco Y, Martinez-Heras E, Solana E, Pulido-Valdeolivas I, Martinez-Lapiscina EH, Garcia-Ojalvo J, Villoslada P.

2023

doi:10.1101/2023.02.26.530153.

Multicellular factor analysis of single-cell data for a tissue-centric understanding of disease

Ramirez Flores RO, Lanzer JD, Dimitrov D, Velten B, Saez-Rodriguez J.

2023

doi:10.1101/2023.02.23.529642.

Phosphoproteomic analysis of metformin signaling in colorectal cancer cells elucidates mechanism of action and potential therapeutic opportunities.

Salovska B, Gao E, Müller-Dott S, Li W, Cordon CC, Wang S, Dugourd A, Rosenberger G, Saez-Rodriguez J, Liu Y.

Clin Transl Med, 2023

doi:10.1002/ctm2.1179.

Charting the Heterogeneity of Colorectal Cancer Consensus Molecular Subtypes using Spatial Transcriptomics

Valdeolivas A, Amberg B, Giroud N, Richardson M, Gálvez EJ, Badillo S, Julien-Laferrière A, Turos D, von Voithenberg LV, Wells I, Lo AA, Yángüez E, Das Thakur M, Bscheider M, Sultan M, Kumpesa N, Jacobsen B, Bergauer T, Saez-Rodriguez J, Rottenberg S, Schwalie PC, Hahn K.

2023

doi:10.1101/2023.01.23.525135.

Pan-Cancer landscape of protein activities identifies drivers of signalling dysregulation and patient survival.

Sousa A, Dugourd A, Memon D, Petursson B, Petsalaki E, Saez-Rodriguez J, Beltrao P.

Mol Syst Biol, 2023

doi:10.15252/msb.202110631.

A Network-based Transcriptomic Landscape of HepG2 cells to Uncover Causal Gene Cytotoxicity Interactions Underlying Drug-Induced Liver Injury

Wijaya LS, Gabor A, Pot IE, van de Have L, Saez-Rodriguez J, Stevens JL, Le Dévédec SE, Callegaro G, van de Water B.

2023

doi:10.1101/2023.01.16.524182.

A Network medicine approach to study comorbidities in heart failure with preserved ejection fraction

Lanzer JD, Valdeolivas A, Pepin M, Hund H, Backs J, Friederich H, Schultz JH, Saez-Rodriguez J, Levinson RT.

2023

doi:10.21203/rs.3.rs-2429581/v1.

Predicting disease severity in Multiple Sclerosis using multimodal data and machine learning

Andorra M, Freire A, Zubizarreta I, de Rosbo NK, Bos SD, Rinas M, Høgestøl EA, Benavent SAR, Berge T, Brune-Ingebretse S, Ivaldi F, Cellerino M, Pardini M, Vila G, Pulido-Valdeolivas I, Martinez-Lapiscina EH, Llufriu S, Saiz A, Blanco Y, Martinez-Heras E, Solana E, Bäcker-Koduah P, Behrens J, Kuchling J, Asseyer S, Scheel M, Chien C, Zimmermann H, Motamedi S, Kauer-Bonin J, Brandt A, Saez-Rodriguez J, Alexopoulos L, Paul F, Harbo HF, Shams H, Oksenberg J, Uccelli A, Baeza-Yates R, Villoslada P.

2023

doi:10.21203/rs.3.rs-2414345/v1.

decoupleR: ensemble of computational methods to infer biological activities from omics data.

Badia-I-Mompel P, Vélez Santiago J, Braunger J, Geiss C, Dimitrov D, Müller-Dott S, Taus P, Dugourd A, Holland CH, Ramirez Flores RO, Saez-Rodriguez J.

Bioinform Adv, 2022

doi:10.1093/bioadv/vbac016.

Pre-analytical processing of plasma and serum samples for combined proteome and metabolome analysis.

Gegner HM, Naake T, Dugourd A, Müller T, Czernilofsky F, Kliewer G, Jäger E, Helm B, Kunze-Rohrbach N, Klingmüller U, Hopf C, Müller-Tidow C, Dietrich S, Saez-Rodriguez J, Huber W, Hell R, Poschet G, Krijgsveld J.

Front Mol Biosci, 2022

doi:10.3389/fmolb.2022.961448.

Dissecting CD8+ T cell pathology of severe SARS-CoV-2 infection by single-cell immunoprofiling.

Schreibing F, Hannani MT, Kim H, Nagai JS, Ticconi F, Fewings E, Bleckwehl T, Begemann M, Torow N, Kuppe C, Kurth I, Kranz J, Frank D, Anslinger TM, Ziegler P, Kraus T, Enczmann J, Balz V, Windhofer F, Balfanz P, Kurts C, Marx G, Marx N, Dreher M, Schneider RK, Saez-Rodriguez J, Costa I, Hayat S, Kramann R.

Front Immunol, 2022

doi:10.3389/fimmu.2022.1066176.

Dynamic partitioning of branched-chain amino acids-derived nitrogen supports renal cancer progression.

Sciacovelli M, Dugourd A, Jimenez LV, Yang M, Nikitopoulou E, Costa ASH, Tronci L, Caraffini V, Rodrigues P, Schmidt C, Ryan DG, Young T, Zecchini VR, Rossi SH, Massie C, Lohoff C, Masid M, Hatzimanikatis V, Kuppe C, Von Kriegsheim A, Kramann R, Gnanapragasam V, Warren AY, Stewart GD, Erez A, Vanharanta S, Saez-Rodriguez J, Frezza C.

Nat Commun, 2022

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A versatile and interoperable computational framework for the analysis and modeling of COVID-19 disease mechanisms

Niarakis A, Ostaszewski M, Mazein A, Kuperstein I, Kutmon M, Gillespie ME, Funahashi A, Acencio ML, Hemedan A, Aichem M, Klein K, Czauderna T, Burtscher F, Yamada TG, Hiki Y, Hiroi NF, Hu F, Pham N, Ehrhart F, Willighagen EL, Valdeolivas A, Dugourd A, Messina F, Esteban-Medina M, Peña-Chilet M, Rian K, Soliman S, Aghamiri SS, Puniya BL, Naldi A, Helikar T, Singh V, Fernández MF, Bermudez V, Tsirvouli E, Montagud A, Noël V, de Leon MP, Maier D, Bauch A, Gyori BM, Bachman JA, Luna A, Pinero J, Furlong LI, Balaur I, Rougny A, Jarosz Y, Overall RW, Phair R, Perfetto L, Matthews L, Rex DAB, Orlic-Milacic M, Cristobal MGL, De Meulder B, Ravel JM, Jassal B, Satagopam V, Wu G, Golebiewski M, Gawron P, Calzone L, Beckmann JS, Evelo CT, D’Eustachio P, Schreiber F, Saez-Rodriguez J, Dopazo J, Kuiper M, Valencia A, Wolkenhauer O, Kitano H, Barillot E, Auffray C, Balling R, Schneider R, the COVID-19 Disease Map Community.

2022

doi:10.1101/2022.12.17.520865.

B cell expansion hinders the stroma-epithelium regenerative cross talk during mucosal healing.

Frede A, Czarnewski P, Monasterio G, Tripathi KP, Bejarano DA, Ramirez Flores RO, Sorini C, Larsson L, Luo X, Geerlings L, Novella-Rausell C, Zagami C, Kuiper R, Morales RA, Castillo F, Hunt M, Mariano LL, Hu YOO, Engblom C, Lennon-Duménil AM, Mittenzwei R, Westendorf AM, Hövelmeyer N, Lundeberg J, Saez-Rodriguez J, Schlitzer A, Das S, Villablanca EJ.

Immunity, 2022

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Spatial cell type mapping of multiple sclerosis lesions

Lerma-Martin C, Badia-i-Mompel P, Ramirez Flores RO, Sekol P, Hofmann A, Thäwel T, Riedl CJ, Wünnemann F, Ibarra-Arellano MA, Trobisch T, Eisele P, Schapiro D, Haeussler M, Hametner S, Saez-Rodriguez J, Schirmer L.

2022

doi:10.1101/2022.11.03.514906.

Adult human kidney organoids originate from CD24<sup>+</sup> cells and represent an advanced model for adult polycystic kidney disease.

Xu Y, Kuppe C, Perales-Patón J, Hayat S, Kranz J, Abdallah AT, Nagai J, Li Z, Peisker F, Saritas T, Halder M, Menzel S, Hoeft K, Kenter A, Kim H, van Roeyen CRC, Lehrke M, Moellmann J, Speer T, Buhl EM, Hoogenboezem R, Boor P, Jansen J, Knopp C, Kurth I, Smeets B, Bindels E, Reinders MEJ, Baan C, Gribnau J, Hoorn EJ, Steffens J, Huber TB, Costa I, Floege J, Schneider RK, Saez-Rodriguez J, Freedman BS, Kramann R.

Nat Genet, 2022

doi:10.1038/s41588-022-01202-z.

A microfluidic Braille valve platform for on-demand production, combinatorial screening and sorting of chemically distinct droplets.

Utharala R, Grab A, Vafaizadeh V, Peschke N, Ballinger M, Turei D, Tuechler N, Ma W, Ivanova O, Ortiz AG, Saez-Rodriguez J, Merten CA.

Nat Protoc, 2022

doi:10.1038/s41596-022-00740-4.

Cross-regional homeostatic and reactive glial signatures in multiple sclerosis.

Trobisch T, Zulji A, Stevens NA, Schwarz S, Wischnewski S, Öztürk M, Perales-Patón J, Haeussler M, Saez-Rodriguez J, Velmeshev D, Schirmer L.

Acta Neuropathol, 2022

doi:10.1007/s00401-022-02497-2.

Compartments in medulloblastoma with extensive nodularity are connected through differentiation along the granular precursor lineage

Ghasemi DR, Okonechnikov K, Rademacher A, Tirier S, Maass KK, Schumacher H, Sundheimer J, Statz B, Rifaioglu AS, Bauer K, Schumacher S, Bortolomeazzi M, Giangaspero F, Ernst KJ, Saez-Rodriguez J, Jones DTW, Kawauchi D, Mallm J, Rippe K, Korshunov A, Pfister SM, Pajtler KW.

2022

doi:10.1101/2022.09.02.506321.

Spatial multi-omic map of human myocardial infarction.

Kuppe C, Ramirez Flores RO, Li Z, Hayat S, Levinson RT, Liao X, Hannani MT, Tanevski J, Wünnemann F, Nagai JS, Halder M, Schumacher D, Menzel S, Schäfer G, Hoeft K, Cheng M, Ziegler S, Zhang X, Peisker F, Kaesler N, Saritas T, Xu Y, Kassner A, Gummert J, Morshuis M, Amrute J, Veltrop RJA, Boor P, Klingel K, Van Laake LW, Vink A, Hoogenboezem RM, Bindels EMJ, Schurgers L, Sattler S, Schapiro D, Schneider RK, Lavine K, Milting H, Costa IG, Saez-Rodriguez J, Kramann R.

Nature, 2022

doi:10.1038/s41586-022-05060-x.

Phosphoproteomics of primary AML patient samples reveals rationale for AKT combination therapy and p53 context to overcome selinexor resistance.

Emdal KB, Palacio-Escat N, Wigerup C, Eguchi A, Nilsson H, Bekker-Jensen DB, Rönnstrand L, Kazi JU, Puissant A, Itzykson R, Saez-Rodriguez J, Masson K, Blume-Jensen P, Olsen JV.

Cell Rep, 2022

doi:10.1016/j.celrep.2022.111177.

Combi-seq for multiplexed transcriptome-based profiling of drug combinations using deterministic barcoding in single-cell droplets.

Mathur L, Szalai B, Du NH, Utharala R, Ballinger M, Landry JJM, Ryckelynck M, Benes V, Saez-Rodriguez J, Merten CA.

Nat Commun, 2022

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Integrating knowledge and omics to decipher mechanisms via large-scale models of signaling networks.

Garrido-Rodriguez M, Zirngibl K, Ivanova O, Lobentanzer S, Saez-Rodriguez J.

Mol Syst Biol, 2022

doi:10.15252/msb.202211036.

Imbalanced gut microbiota fuels hepatocellular carcinoma development by shaping the hepatic inflammatory microenvironment.

Schneider KM, Mohs A, Gui W, Galvez EJC, Candels LS, Hoenicke L, Muthukumarasamy U, Holland CH, Elfers C, Kilic K, Schneider CV, Schierwagen R, Strnad P, Wirtz TH, Marschall HU, Latz E, Lelouvier B, Saez-Rodriguez J, de Vos W, Strowig T, Trebicka J, Trautwein C.

Nat Commun, 2022

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Deep Phosphoproteomic Elucidation of Metformin-Signaling in Heterogenous Colorectal Cancer Cells

Salovska B, Gao E, Müller-Dott S, Li W, Dugourd A, Rosenberger G, Saez-Rodriguez J, Liu Y.

2022

doi:10.1101/2022.07.07.499038.

Cancer-associated fibroblasts require proline synthesis by PYCR1 for the deposition of pro-tumorigenic extracellular matrix.

Kay EJ, Paterson K, Riera-Domingo C, Sumpton D, Däbritz JHM, Tardito S, Boldrini C, Hernandez-Fernaud JR, Athineos D, Dhayade S, Stepanova E, Gjerga E, Neilson LJ, Lilla S, Hedley A, Koulouras G, McGregor G, Jamieson C, Johnson RM, Park M, Kirschner K, Miller C, Kamphorst JJ, Loayza-Puch F, Saez-Rodriguez J, Mazzone M, Blyth K, Zagnoni M, Zanivan S.

Nat Metab, 2022

doi:10.1038/s42255-022-00582-0.

Reconstructing the functional effect of<i>TP53</i>somatic mutations on its regulon using causal signalling network modelling

Triantafyllidis CP, Barberis A, Cuervo AM, Gjerga E, Charlton P, Hartley F, Van Bijsterveldt L, Rodriguez JS, Buffa FM.

2022

doi:10.1101/2022.06.23.497293.

Comparison of methods and resources for cell-cell communication inference from single-cell RNA-Seq data.

Dimitrov D, Türei D, Garrido-Rodriguez M, Burmedi PL, Nagai JS, Boys C, Ramirez Flores RO, Kim H, Szalai B, Costa IG, Valdeolivas A, Dugourd A, Saez-Rodriguez J.

Nat Commun, 2022

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Community assessment of methods to deconvolve cellular composition from bulk gene expression

White BS, de Reyniès A, Newman AM, Waterfall JJ, Lamb A, Petitprez F, Valdeolivas A, Lin Y, Li H, Xiao X, Wang S, Zheng F, Yang W, Yu R, Guerrero-Gimenez ME, Catania CA, Lang BJ, Domanskyi S, Bertus TJ, Piermarocchi C, Monaco G, Caruso FP, Ceccarelli M, Yu T, Guo X, Coller J, Maecker H, Duault C, Shokoohi V, Patel S, Liliental JE, Simon S, Saez-Rodriguez J, Heiser LM, Guinney J, Gentles AJ, Tumor Deconvolution DREAM Challenge consortium.

2022

doi:10.1101/2022.06.03.494221.

Proteomic Dynamics of Breast Cancers Identifies Potential Therapeutic Protein Targets

Sun R, Zhu Y, Sayad A, Ge W, Luna A, Liang S, Segura LT, Rajapakse VN, Yu C, Zhang H, Fang J, Wu F, Xie H, Saez-Rodriguez J, Ying H, Reinhold WC, Sander C, Pommier Y, Neel BG, Guo T, Aebersold R.

2022

doi:10.1101/2022.06.03.494776.

Reducing lipid bilayer stress by monounsaturated fatty acids protects renal proximal tubules in diabetes.

Pérez-Martí A, Ramakrishnan S, Li J, Dugourd A, Molenaar MR, De La Motte LR, Grand K, Mansouri A, Parisot M, Lienkamp SS, Saez-Rodriguez J, Simons M.

Elife, 2022

doi:10.7554/elife.74391.

Mapping the epithelial-immune cell interactome upon infection in the gut and the upper airways.

Poletti M, Treveil A, Csabai L, Gul L, Modos D, Madgwick M, Olbei M, Bohar B, Valdeolivas A, Turei D, Verstockt B, Triana S, Alexandrov T, Saez-Rodriguez J, Stanifer ML, Boulant S, Korcsmaros T.

NPJ Syst Biol Appl, 2022

doi:10.1038/s41540-022-00224-x.

Pre-analytical processing of plasma and serum samples for combined proteome and metabolome analysis

Gegner HM, Naake T, Dugourd A, Müller T, Czernilofsky F, Kliewer G, Jäger E, Helm B, Kunze-Rohrbach N, Klingmüller U, Hopf C, Müller-Tidow C, Dietrich S, Saez-Rodriguez J, Huber W, Hell R, Poschet G, Krijgsveld J.

2022

doi:10.1101/2022.04.26.489520.

Explainable multiview framework for dissecting spatial relationships from highly multiplexed data.

Tanevski J, Flores ROR, Gabor A, Schapiro D, Saez-Rodriguez J.

Genome Biol, 2022

doi:10.1186/s13059-022-02663-5.

Computational drug repurposing against SARS-CoV-2 reveals plasma membrane cholesterol depletion as key factor of antiviral drug activity.

Barsi S, Papp H, Valdeolivas A, Tóth DJ, Kuczmog A, Madai M, Hunyady L, Várnai P, Saez-Rodriguez J, Jakab F, Szalai B.

PLoS Comput Biol, 2022

doi:10.1371/journal.pcbi.1010021.

Molecular consequences of SARS-CoV-2 liver tropism.

Wanner N, Andrieux G, Badia-I-Mompel P, Edler C, Pfefferle S, Lindenmeyer MT, Schmidt-Lauber C, Czogalla J, Wong MN, Okabayashi Y, Braun F, Lütgehetmann M, Meister E, Lu S, Noriega MLM, Günther T, Grundhoff A, Fischer N, Bräuninger H, Lindner D, Westermann D, Haas F, Roedl K, Kluge S, Addo MM, Huber S, Lohse AW, Reiser J, Ondruschka B, Sperhake JP, Saez-Rodriguez J, Boerries M, Hayek SS, Aepfelbacher M, Scaturro P, Puelles VG, Huber TB.

Nat Metab, 2022

doi:10.1038/s42255-022-00552-6.

Patient-specific Boolean models of signalling networks guide personalised treatments.

Montagud A, Béal J, Tobalina L, Traynard P, Subramanian V, Szalai B, Alföldi R, Puskás L, Valencia A, Barillot E, Saez-Rodriguez J, Calzone L.

Elife, 2022

doi:10.7554/elife.72626.

The spatial transcriptomic landscape of the healing mouse intestine following damage.

Parigi SM, Larsson L, Das S, Ramirez Flores RO, Frede A, Tripathi KP, Diaz OE, Selin K, Morales RA, Luo X, Monasterio G, Engblom C, Gagliani N, Saez-Rodriguez J, Lundeberg J, Villablanca EJ.

Nat Commun, 2022

doi:10.1038/s41467-022-28497-0.

FUNKI: interactive functional footprint-based analysis of omics data.

Hernansaiz-Ballesteros R, Holland CH, Dugourd A, Saez-Rodriguez J.

Bioinformatics, 2022

doi:10.1093/bioinformatics/btac055.

A community challenge for a pancancer drug mechanism of action inference from perturbational profile data.

Douglass EF, Allaway RJ, Szalai B, Wang W, Tian T, Fernández-Torras A, Realubit R, Karan C, Zheng S, Pessia A, Tanoli Z, Jafari M, Wan F, Li S, Xiong Y, Duran-Frigola M, Bertoni M, Badia-I-Mompel P, Mateo L, Guitart-Pla O, Chung V, DREAM CTD-squared Pancancer Drug Activity Challenge Consortium, Tang J, Zeng J, Aloy P, Saez-Rodriguez J, Guinney J, Gerhard DS, Califano A.

Cell Rep Med, 2022

doi:10.1016/j.xcrm.2021.100492.

Two heads are better than one: current landscape of integrating QSP and machine learning : An ISoP QSP SIG white paper by the working group on the integration of quantitative systems pharmacology and machine learning.

Zhang T, Androulakis IP, Bonate P, Cheng L, Helikar T, Parikh J, Rackauckas C, Subramanian K, Cho CR, Working Group.

J Pharmacokinet Pharmacodyn, 2022

doi:10.1007/s10928-022-09805-z.

Stabilization but No Functional Influence of HIF-1α Expression in the Intestinal Epithelium during Salmonella Typhimurium Infection.

Robrahn L, Dupont A, Jumpertz S, Zhang K, Holland CH, Guillaume J, Rappold S, Roth J, Cerovic V, Saez-Rodriguez J, Hornef MW, Cramer T.

Infect Immun, 2022

doi:10.1128/iai.00222-21.

MAGED2 controls vasopressin-induced aquaporin-2 expression in collecting duct cells.

Reusch B, Bartram MP, Dafinger C, Palacio-Escat N, Wenzel A, Fenton RA, Saez-Rodriguez J, Schermer B, Benzing T, Altmüller J, Beck BB, Rinschen MM.

J Proteomics, 2022

doi:10.1016/j.jprot.2021.104424.

Transcriptomic Cross-Species Analysis of Chronic Liver Disease Reveals Consistent Regulation Between Humans and Mice.

Holland CH, Ramirez Flores RO, Myllys M, Hassan R, Edlund K, Hofmann U, Marchan R, Cadenas C, Reinders J, Hoehme S, Seddek AL, Dooley S, Keitel V, Godoy P, Begher-Tibbe B, Trautwein C, Rupp C, Mueller S, Longerich T, Hengstler JG, Saez-Rodriguez J, Ghallab A.

Hepatol Commun, 2022

doi:10.1002/hep4.1797.

Deficiency of myeloid PHD proteins aggravates atherogenesis via macrophage apoptosis and paracrine fibrotic signalling.

van Kuijk K, Demandt JAF, Perales-Patón J, Theelen TL, Kuppe C, Marsch E, de Bruijn J, Jin H, Gijbels MJ, Matic L, Mees BME, Reutelingsperger CPM, Hedin U, Biessen EAL, Carmeliet P, Baker AH, Kramann RK, Schurgers LJ, Saez-Rodriguez J, Sluimer JC.

Cardiovasc Res, 2022

doi:10.1093/cvr/cvab152.

Experimental and computational technologies to dissect the kidney at the single-cell level.

Kuppe C, Perales-Patón J, Saez-Rodriguez J, Kramann R.

Nephrol Dial Transplant, 2022

doi:10.1093/ndt/gfaa233.

COVID-19 Disease Map, a computational knowledge repository of virus-host interaction mechanisms.

Ostaszewski M, Niarakis A, Mazein A, Kuperstein I, Phair R, Orta-Resendiz A, Singh V, Aghamiri SS, Acencio ML, Glaab E, Ruepp A, Fobo G, Montrone C, Brauner B, Frishman G, Monraz Gómez LC, Somers J, Hoch M, Kumar Gupta S, Scheel J, Borlinghaus H, Czauderna T, Schreiber F, Montagud A, Ponce de Leon M, Funahashi A, Hiki Y, Hiroi N, Yamada TG, Dräger A, Renz A, Naveez M, Bocskei Z, Messina F, Börnigen D, Fergusson L, Conti M, Rameil M, Nakonecnij V, Vanhoefer J, Schmiester L, Wang M, Ackerman EE, Shoemaker JE, Zucker J, Oxford K, Teuton J, Kocakaya E, Summak GY, Hanspers K, Kutmon M, Coort S, Eijssen L, Ehrhart F, Rex DAB, Slenter D, Martens M, Pham N, Haw R, Jassal B, Matthews L, Orlic-Milacic M, Senff-Ribeiro A, Rothfels K, Shamovsky V, Stephan R, Sevilla C, Varusai T, Ravel JM, Fraser R, Ortseifen V, Marchesi S, Gawron P, Smula E, Heirendt L, Satagopam V, Wu G, Riutta A, Golebiewski M, Owen S, Goble C, Hu X, Overall RW, Maier D, Bauch A, Gyori BM, Bachman JA, Vega C, Grouès V, Vazquez M, Porras P, Licata L, Iannuccelli M, Sacco F, Nesterova A, Yuryev A, de Waard A, Turei D, Luna A, Babur O, Soliman S, Valdeolivas A, Esteban-Medina M, Peña-Chilet M, Rian K, Helikar T, Puniya BL, Modos D, Treveil A, Olbei M, De Meulder B, Ballereau S, Dugourd A, Naldi A, Noël V, Calzone L, Sander C, Demir E, Korcsmaros T, Freeman TC, Augé F, Beckmann JS, Hasenauer J, Wolkenhauer O, Willighagen EL, Pico AR, Evelo CT, Gillespie ME, Stein LD, Hermjakob H, D'Eustachio P, Saez-Rodriguez J, Dopazo J, Valencia A, Kitano H, Barillot E, Auffray C, Balling R, Schneider R, COVID-19 Disease Map Community.

Mol Syst Biol, 2021

doi:10.15252/msb.202110851.

decoupleR: Ensemble of computational methods to infer biological activities from omics data

Badia-i-Mompel P, Vélez J, Braunger J, Geiss C, Dimitrov D, Müller-Dott S, Taus P, Dugourd A, Holland CH, Ramirez Flores RO, Saez-Rodriguez J.

2021

doi:10.1101/2021.11.04.467271.

COVID19 Disease Map, a computational knowledge repository of virus-host interaction mechanisms.

Ostaszewski M, Niarakis A, Mazein A, Kuperstein I, Phair R, Orta-Resendiz A, Singh V, Aghamiri SS, Acencio ML, Glaab E, Ruepp A, Fobo G, Montrone C, Brauner B, Frishman G, Monraz Gómez LC, Somers J, Hoch M, Kumar Gupta S, Scheel J, Borlinghaus H, Czauderna T, Schreiber F, Montagud A, Ponce de Leon M, Funahashi A, Hiki Y, Hiroi N, Yamada TG, Dräger A, Renz A, Naveez M, Bocskei Z, Messina F, Börnigen D, Fergusson L, Conti M, Rameil M, Nakonecnij V, Vanhoefer J, Schmiester L, Wang M, Ackerman EE, Shoemaker JE, Zucker J, Oxford K, Teuton J, Kocakaya E, Summak GY, Hanspers K, Kutmon M, Coort S, Eijssen L, Ehrhart F, Rex DAB, Slenter D, Martens M, Pham N, Haw R, Jassal B, Matthews L, Orlic-Milacic M, Senff Ribeiro A, Rothfels K, Shamovsky V, Stephan R, Sevilla C, Varusai T, Ravel JM, Fraser R, Ortseifen V, Marchesi S, Gawron P, Smula E, Heirendt L, Satagopam V, Wu G, Riutta A, Golebiewski M, Owen S, Goble C, Hu X, Overall RW, Maier D, Bauch A, Gyori BM, Bachman JA, Vega C, Grouès V, Vazquez M, Porras P, Licata L, Iannuccelli M, Sacco F, Nesterova A, Yuryev A, de Waard A, Turei D, Luna A, Babur O, Soliman S, Valdeolivas A, Esteban-Medina M, Peña-Chilet M, Rian K, Helikar T, Puniya BL, Modos D, Treveil A, Olbei M, De Meulder B, Ballereau S, Dugourd A, Naldi A, Noël V, Calzone L, Sander C, Demir E, Korcsmaros T, Freeman TC, Augé F, Beckmann JS, Hasenauer J, Wolkenhauer O, Wilighagen EL, Pico AR, Evelo CT, Gillespie ME, Stein LD, Hermjakob H, D'Eustachio P, Saez-Rodriguez J, Dopazo J, Valencia A, Kitano H, Barillot E, Auffray C, Balling R, Schneider R, COVID-19 Disease Map Community.

Mol Syst Biol, 2021

doi:10.15252/msb.202110387.

Cell-to-cell and type-to-type heterogeneity of signaling networks: insights from the crowd.

Gabor A, Tognetti M, Driessen A, Tanevski J, Guo B, Cao W, Shen H, Yu T, Chung V, Single Cell Signaling in Breast Cancer DREAM Consortium members, Bodenmiller B, Saez-Rodriguez J.

Mol Syst Biol, 2021

doi:10.15252/msb.202110402.

The human hepatocyte TXG-MAPr: gene co-expression network modules to support mechanism-based risk assessment.

Callegaro G, Kunnen SJ, Trairatphisan P, Grosdidier S, Niemeijer M, den Hollander W, Guney E, Piñero Gonzalez J, Furlong L, Webster YW, Saez-Rodriguez J, Sutherland JJ, Mollon J, Stevens JL, van de Water B.

Arch Toxicol, 2021

doi:10.1007/s00204-021-03141-w.

Systems approach reveals distinct and shared signaling networks of the four PGE<sub>2</sub> receptors in T cells.

Lone AM, Giansanti P, Jørgensen MJ, Gjerga E, Dugourd A, Scholten A, Saez-Rodriguez J, Heck AJR, Taskén K.

Sci Signal, 2021

doi:10.1126/scisignal.abc8579.

Combi-Seq: Multiplexed transcriptome-based profiling of drug combinations using deterministic barcoding in single-cell droplets

Mathur L, Szalai B, Utharala R, Ballinger M, Landry J, Ryckelynck M, Benes V, Saez-Rodriguez J, Merten C.

2021

doi:10.1101/2021.09.16.460212.

Nitrogen partitioning between branched-chain amino acids and urea cycle enzymes sustains renal cancer progression

Sciacovelli M, Dugourd A, Jimenez LV, Yang M, Nikitopoulou E, Costa AS, Tronci L, Caraffini V, Rodrigues P, Schmidt C, Ryan D, Young T, Zecchini VR, Rossi SH, Massie C, Lohoff C, Barcon MM, Hatzimanikatis V, Kuppe C, Von Kriegsheim A, Kramann R, Gnanapragasam V, Warren AY, Stewart GD, Erez A, Vanharanta S, Saez-Rodriguez J, Frezza C.

2021

doi:10.1101/2021.09.17.460635.

SREBP1-induced fatty acid synthesis depletes macrophages antioxidant defences to promote their alternative activation.

Bidault G, Virtue S, Petkevicius K, Jolin HE, Dugourd A, Guénantin AC, Leggat J, Mahler-Araujo B, Lam BYH, Ma MK, Dale M, Carobbio S, Kaser A, Fallon PG, Saez-Rodriguez J, McKenzie ANJ, Vidal-Puig A.

Nat Metab, 2021

doi:10.1038/s42255-021-00440-5.

Medial Arterial Calcification: JACC State-of-the-Art Review.

Lanzer P, Hannan FM, Lanzer JD, Janzen J, Raggi P, Furniss D, Schuchardt M, Thakker R, Fok PW, Saez-Rodriguez J, Millan A, Sato Y, Ferraresi R, Virmani R, St Hilaire C.

J Am Coll Cardiol, 2021

doi:10.1016/j.jacc.2021.06.049.

Increasing triacylglycerol formation and lipid storage by unsaturated lipids protects renal proximal tubules in diabetes

Pérez-Martí A, Ramakrishnan S, Li J, Dugourd A, Molenaar MR, De La Motte LR, Grand K, Mansouri A, Parisot M, Lienkamp SS, Saez-Rodriguez J, Simons M.

2021

doi:10.1101/2021.09.07.459360.

Computational drug repurposing against SARS-CoV-2 reveals plasma membrane cholesterol depletion as key factor of antiviral drug activity

Barsi S, Papp H, Urbelz AV, Tóth DJ, Kuczmog A, Madai M, Hunyady L, Várnai P, Saez-Rodriguez J, Jakab F, Szalai B.

2021

doi:10.1101/2021.09.10.459786.

Partial Inhibition of the 6-Phosphofructo-2-Kinase/Fructose-2,6-Bisphosphatase-3 (PFKFB3) Enzyme in Myeloid Cells Does Not Affect Atherosclerosis.

Tillie RJHA, De Bruijn J, Perales-Patón J, Temmerman L, Ghosheh Y, Van Kuijk K, Gijbels MJ, Carmeliet P, Ley K, Saez-Rodriguez J, Sluimer JC.

Front Cell Dev Biol, 2021

doi:10.3389/fcell.2021.695684.

Reprogramming of the intestinal epithelial-immune cell interactome during SARS-CoV-2 infection

Poletti M, Treveil A, Csabai L, Gul L, Modos D, Madgwick M, Olbei M, Bohar B, Valdeolivas A, Turei D, Verstockt B, Triana S, Alexandrov T, Saez-Rodriguez J, Stanifer ML, Boulant S, Korcsmaros T.

2021

doi:10.1101/2021.08.09.455656.

Patient-specific Boolean models of signaling networks guide personalized treatments

Montagud A, Béal J, Tobalina L, Traynard P, Subramanian V, Szalai B, Alföldi R, Puskás L, Valencia A, Barillot E, Saez-Rodriguez J, Calzone L.

2021

doi:10.1101/2021.07.28.454126.

Explainable multi-view framework for dissecting intercellular signaling from highly multiplexed spatial data

Tanevski J, Gabor A, Flores RR, Schapiro D, Saez-Rodriguez J.

2021

doi:10.21203/rs.3.rs-735362/v1.

Prediction of combination therapies based on topological modeling of the immune signaling network in multiple sclerosis.

Bernardo-Faura M, Rinas M, Wirbel J, Pertsovskaya I, Pliaka V, Messinis DE, Vila G, Sakellaropoulos T, Faigle W, Stridh P, Behrens JR, Olsson T, Martin R, Paul F, Alexopoulos LG, Villoslada P, Saez-Rodriguez J.

Genome Med, 2021

doi:10.1186/s13073-021-00925-8.

Contextualization of causal regulatory networks from toxicogenomics data applied to drug-induced liver injury.

Trairatphisan P, de Souza TM, Kleinjans J, Jennen D, Saez-Rodriguez J.

Toxicol Lett, 2021

doi:10.1016/j.toxlet.2021.06.020.

Cell-cell Communication Inference from Single-cell RNA-Seq Data: a Comparison of Methods and Resources

Dimitrov D, Türei D, Boys C, Nagai J, Flores RR, Kim H, Szalai B, Costa I, Dugourd A, Valdeolivas A, Rodriguez JS.

2021

doi:10.21203/rs.3.rs-634687/v1.

The spatial transcriptomic landscape of the healing intestine following damage

Parigi SM, Larsson L, Das S, Ramirez Flores RO, Frede A, Tripathi KP, Diaz OE, Selin K, Morales RA, Luo X, Monasterio G, Engblom C, Gagliani N, Saez-Rodriguez J, Lundeberg J, Villablanca EJ.

2021

doi:10.1101/2021.07.01.450768.

SysMod: the ISCB community for data-driven computational modelling and multi-scale analysis of biological systems.

Dräger A, Helikar T, Barberis M, Birtwistle M, Calzone L, Chaouiya C, Hasenauer J, Karr JR, Niarakis A, Rodríguez Martínez M, Saez-Rodriguez J, Thakar J.

Bioinformatics, 2021

doi:10.1093/bioinformatics/btab229.

Deep spatial profiling of human COVID-19 brains reveals neuroinflammation with distinct microanatomical microglia-T-cell interactions.

Schwabenland M, Salié H, Tanevski J, Killmer S, Lago MS, Schlaak AE, Mayer L, Matschke J, Püschel K, Fitzek A, Ondruschka B, Mei HE, Boettler T, Neumann-Haefelin C, Hofmann M, Breithaupt A, Genc N, Stadelmann C, Saez-Rodriguez J, Bronsert P, Knobeloch KP, Blank T, Thimme R, Glatzel M, Prinz M, Bengsch B.

Immunity, 2021

doi:10.1016/j.immuni.2021.06.002.

A comprehensive database for integrated analysis of omics data in autoimmune diseases.

Martorell-Marugán J, López-Domínguez R, García-Moreno A, Toro-Domínguez D, Villatoro-García JA, Barturen G, Martín-Gómez A, Troule K, Gómez-López G, Al-Shahrour F, González-Rumayor V, Peña-Chilet M, Dopazo J, Sáez-Rodríguez J, Alarcón-Riquelme ME, Carmona-Sáez P.

BMC Bioinformatics, 2021

doi:10.1186/s12859-021-04268-4.

New insights into the mechanisms underlying 5-fluorouracil-induced intestinal toxicity based on transcriptomic and metabolomic responses in human intestinal organoids.

Rodrigues D, de Souza T, Coyle L, Di Piazza M, Herpers B, Ferreira S, Zhang M, Vappiani J, Sévin DC, Gabor A, Lynch A, Chung SW, Saez-Rodriguez J, Jennen DGJ, Kleinjans JCS, de Kok TM.

Arch Toxicol, 2021

doi:10.1007/s00204-021-03092-2.

Advances in systems biology modeling: 10 years of crowdsourcing DREAM challenges.

Meyer P, Saez-Rodriguez J.

Cell Syst, 2021

doi:10.1016/j.cels.2021.05.015.

Pan-Cancer landscape of protein activities identifies drivers of signalling dysregulation and patient survival

Sousa A, Dugourd A, Memon D, Petursson B, Petsalaki E, Saez-Rodriguez J, Beltrao P.

2021

doi:10.1101/2021.06.09.447741.

Comparison of Resources and Methods to infer Cell-Cell Communication from Single-cell RNA Data

Dimitrov D, Türei D, Boys C, Nagai JS, Ramirez Flores RO, Kim H, Szalai B, Costa IG, Dugourd A, Valdeolivas A, Saez-Rodriguez J.

2021

doi:10.1101/2021.05.21.445160.

The human hepatocyte TXG-MAPr: WGCNA transcriptomic modules to support mechanism-based risk assessment

Callegaro G, Kunnen SJ, Trairatphisan P, Grosdidier S, Niemeijer M, den Hollander W, Guney E, Piñero Gonzalez J, Furlong L, Webster YW, Saez-Rodriguez J, Sutherland JJ, Mollon J, Stevens JL, van de Water B.

2021

doi:10.1101/2021.05.17.444463.

Correction to: How will artificial intelligence and bioinformatics change our understanding of IgA Nephropathy in the next decade?

Bülow RD, Dimitrov D, Boor P, Saez-Rodriguez J.

Semin Immunopathol, 2021

doi:10.1007/s00281-021-00858-9.

Integration of temporal single cell cellular stress response activity with logic-ODE modeling reveals activation of ATF4-CHOP axis as a critical predictor of drug-induced liver injury.

Wijaya LS, Trairatphisan P, Gabor A, Niemeijer M, Keet J, Alcalà Morera A, Snijders KE, Wink S, Yang H, Schildknecht S, Stevens JL, Bouwman P, Kamp H, Hengstler J, Beltman J, Leist M, Le Dévédec S, Saez-Rodriguez J, van de Water B.

Biochem Pharmacol, 2021

doi:10.1016/j.bcp.2021.114591.

Deciphering the signaling network of breast cancer improves drug sensitivity prediction.

Tognetti M, Gabor A, Yang M, Cappelletti V, Windhager J, Rueda OM, Charmpi K, Esmaeilishirazifard E, Bruna A, de Souza N, Caldas C, Beyer A, Picotti P, Saez-Rodriguez J, Bodenmiller B.

Cell Syst, 2021

doi:10.1016/j.cels.2021.04.002.

Transcription Factor Activity Inference in Systemic Lupus Erythematosus.

Lopez-Dominguez R, Toro-Dominguez D, Martorell-Marugan J, Garcia-Moreno A, Holland CH, Saez-Rodriguez J, Goldman D, Petri MA, Alarcon-Riquelme ME, Carmona-Saez P.

Life (Basel), 2021

doi:10.3390/life11040299.

How will artificial intelligence and bioinformatics change our understanding of IgA Nephropathy in the next decade?

Bülow RD, Dimitrov D, Boor P, Saez-Rodriguez J.

Semin Immunopathol, 2021

doi:10.1007/s00281-021-00847-y.

Reusability and composability in process description maps: RAS-RAF-MEK-ERK signalling.

Mazein A, Rougny A, Karr JR, Saez-Rodriguez J, Ostaszewski M, Schneider R.

Brief Bioinform, 2021

doi:10.1093/bib/bbab103.

Corrigendum: Benchmark and integration of resources for the estimation of human transcription factor activities.

Garcia-Alonso L, Holland CH, Ibrahim MM, Turei D, Saez-Rodriguez J.

Genome Res, 2021

doi:10.1101/gr.275408.121.

Consensus Transcriptional Landscape of Human End-Stage Heart Failure.

Ramirez Flores RO, Lanzer JD, Holland CH, Leuschner F, Most P, Schultz JH, Levinson RT, Saez-Rodriguez J.

J Am Heart Assoc, 2021

doi:10.1161/jaha.120.019667.

Macrophage beta2-adrenergic receptor is dispensable for the adipose tissue inflammation and function.

Petkevicius K, Bidault G, Virtue S, Newland SA, Dale M, Dugourd A, Saez-Rodriguez J, Mallat Z, Vidal-Puig A.

Mol Metab, 2021

doi:10.1016/j.molmet.2021.101220.

Cell-to-cell and type-to-type heterogeneity of signaling networks: Insights from the crowd

Gabor A, Tognetti M, Driessen A, Tanevski J, Guo B, Cao W, Shen H, Yu T, Chung V, Bodenmiller B, Saez-Rodriguez J, Single Cell Signaling in Breast Cancer DREAM Consortium members.

2021

doi:10.1101/2021.03.23.436603.

Integrated intra- and intercellular signaling knowledge for multicellular omics analysis.

Türei D, Valdeolivas A, Gul L, Palacio-Escat N, Klein M, Ivanova O, Ölbei M, Gábor A, Theis F, Módos D, Korcsmáros T, Saez-Rodriguez J.

Mol Syst Biol, 2021

doi:10.15252/msb.20209923.

Statistical and Machine Learning Techniques in Human Microbiome Studies: Contemporary Challenges and Solutions.

Moreno-Indias I, Lahti L, Nedyalkova M, Elbere I, Roshchupkin G, Adilovic M, Aydemir O, Bakir-Gungor B, Santa Pau EC, D'Elia D, Desai MS, Falquet L, Gundogdu A, Hron K, Klammsteiner T, Lopes MB, Marcos-Zambrano LJ, Marques C, Mason M, May P, Pašić L, Pio G, Pongor S, Promponas VJ, Przymus P, Saez-Rodriguez J, Sampri A, Shigdel R, Stres B, Suharoschi R, Truu J, Truică CO, Vilne B, Vlachakis D, Yilmaz E, Zeller G, Zomer AL, Gómez-Cabrero D, Claesson MJ.

Front Microbiol, 2021

doi:10.3389/fmicb.2021.635781.

PHONEMeS: Efficient Modeling of Signaling Networks Derived from Large-Scale Mass Spectrometry Data.

Gjerga E, Dugourd A, Tobalina L, Sousa A, Saez-Rodriguez J.

J Proteome Res, 2021

doi:10.1021/acs.jproteome.0c00958.

Dissecting CD8+ T cell pathology of severe SARS-CoV-2 infection by single-cell epitope mapping

Schreibing F, Hannani M, Ticconi F, Fewings E, Nagai JS, Begemann M, Kuppe C, Kurth I, Kranz J, Frank D, Anslinger TM, Ziegler P, Kraus T, Enczmann J, Balz V, Windhofer F, Balfanz P, Kurts C, Marx G, Marx N, Dreher M, Schneider RK, Saez-Rodriguez J, Costa I, Kramann R.

2021

doi:10.1101/2021.03.03.432690.

Contextualization of causal regulatory networks from toxicogenomics data applied to drug-induced liver injury

Trairatphisan P, de Souza TM, Kleinjans J, Jennen D, Saez-Rodriguez J.

2021

doi:10.1101/2021.01.31.429025.

Causal integration of multi-omics data with prior knowledge to generate mechanistic hypotheses.

Dugourd A, Kuppe C, Sciacovelli M, Gjerga E, Gabor A, Emdal KB, Vieira V, Bekker-Jensen DB, Kranz J, Bindels EMJ, Costa ASH, Sousa A, Beltrao P, Rocha M, Olsen JV, Frezza C, Kramann R, Saez-Rodriguez J.

Mol Syst Biol, 2021

doi:10.15252/msb.20209730.

Deep Spatial Profiling of COVID-19 Brains Reveals Neuroinflammation by Compartmentalized Local Immune Cell Interactions and Targets for Intervention

Schwabenland M, Salié H, Tanevski J, Killmer S, Lago MS, Matschke J, Pueschel K, Mei HE, Boettler T, Neumann-Haefelin C, Hofmann M, Breithaupt A, Stadelmann-Nesser C, Saez-Rodriguez J, Knobeloch K, Blank T, Thimme R, Glatzel M, Prinz M, Bengsch B.

2021

doi:10.2139/ssrn.3765620.

Norepinephrine promotes triglyceride storage in macrophages via beta2-adrenergic receptor activation.

Petkevicius K, Bidault G, Virtue S, Jenkins B, van Dierendonck XAMH, Dugourd A, Saez-Rodriguez J, Stienstra R, Koulman A, Vidal-Puig A.

FASEB J, 2021

doi:10.1096/fj.202001101r.

Conditional deletion of HIF-1α provides new insight regarding the murine response to gastrointestinal infection with <i>Salmonella</i> Typhimurium

Robrahn L, Dupont A, Jumpertz S, Zhang K, Holland CH, Guillaume J, Rappold S, Cerovic V, Saez-Rodriguez J, Hornef MW, Cramer T.

2021

doi:10.1101/2021.01.16.426940.

Differential expression of microRNA miR-150-5p in IgA nephropathy as a potential mediator and marker of disease progression.

Pawluczyk IZA, Didangelos A, Barbour SJ, Er L, Becker JU, Martin R, Taylor S, Bhachu JS, Lyons EG, Jenkins RH, Fraser D, Molyneux K, Perales-Patón J, Saez-Rodriguez J, Barratt J.

Kidney Int, 2021

doi:10.1016/j.kint.2020.12.028.

Dynamic 3D proteomes reveal protein functional alterations at high resolution in situ.

Cappelletti V, Hauser T, Piazza I, Pepelnjak M, Malinovska L, Fuhrer T, Li Y, Dörig C, Boersema P, Gillet L, Grossbach J, Dugourd A, Saez-Rodriguez J, Beyer A, Zamboni N, Caflisch A, de Souza N, Picotti P.

Cell, 2021

doi:10.1016/j.cell.2020.12.021.

Hepatocyte-specific NRF2 activation controls fibrogenesis and carcinogenesis in steatohepatitis.

Mohs A, Otto T, Schneider KM, Peltzer M, Boekschoten M, Holland CH, Hudert CA, Kalveram L, Wiegand S, Saez-Rodriguez J, Longerich T, Hengstler JG, Trautwein C.

J Hepatol, 2021

doi:10.1016/j.jhep.2020.09.037.

Decoding myofibroblast origins in human kidney fibrosis.

Kuppe C, Ibrahim MM, Kranz J, Zhang X, Ziegler S, Perales-Patón J, Jansen J, Reimer KC, Smith JR, Dobie R, Wilson-Kanamori JR, Halder M, Xu Y, Kabgani N, Kaesler N, Klaus M, Gernhold L, Puelles VG, Huber TB, Boor P, Menzel S, Hoogenboezem RM, Bindels EMJ, Steffens J, Floege J, Schneider RK, Saez-Rodriguez J, Henderson NC, Kramann R.

Nature, 2021

doi:10.1038/s41586-020-2941-1.

The tissue proteome in the multi-omic landscape of kidney disease.

Rinschen MM, Saez-Rodriguez J.

Nat Rev Nephrol, 2021

doi:10.1038/s41581-020-00348-5.

The Minimum Information about a Molecular Interaction CAusal STatement (MI2CAST).

Touré V, Vercruysse S, Acencio ML, Lovering RC, Orchard S, Bradley G, Casals-Casas C, Chaouiya C, Del-Toro N, Flobak Å, Gaudet P, Hermjakob H, Hoyt CT, Licata L, Lægreid A, Mungall CJ, Niknejad A, Panni S, Perfetto L, Porras P, Pratt D, Saez-Rodriguez J, Thieffry D, Thomas PD, Türei D, Kuiper M.

Bioinformatics, 2021

doi:10.1093/bioinformatics/btaa622.

Setting the basis of best practices and standards for curation and annotation of logical models in biology-highlights of the [BC]2 2019 CoLoMoTo/SysMod Workshop.

Niarakis A, Kuiper M, Ostaszewski M, Malik Sheriff RS, Casals-Casas C, Thieffry D, Freeman TC, Thomas P, Touré V, Noël V, Stoll G, Saez-Rodriguez J, Naldi A, Oshurko E, Xenarios I, Soliman S, Chaouiya C, Helikar T, Calzone L.

Brief Bioinform, 2021

doi:10.1093/bib/bbaa046.

Patient-specific logic models of signaling pathways from screenings on cancer biopsies to prioritize personalized combination therapies.

Eduati F, Jaaks P, Wappler J, Cramer T, Merten CA, Garnett MJ, Saez-Rodriguez J.

Mol Syst Biol, 2020

doi:10.15252/msb.209690.

A Community Challenge for Pancancer Drug Mechanism of Action Inference from Perturbational Profile Data

Douglass EF, Allaway RJ, Szalai B, Wang W, Tian T, Fernández-Torras A, Realubit R, Karan C, Zheng S, Pessia A, Tanoli Z, Jafari M, Wan F, Li S, Xiong Y, Duran-Frigola M, Bertoni M, Badia-i-Mompel P, Mateo L, Guitart-Pla O, Chung V, Tang J, Zeng J, Aloy P, Saez-Rodriguez J, Guinney J, Gerhard DS, Califano A, DREAM CTD-squared Pancancer Drug Activity Challenge Consortium.

2020

doi:10.1101/2020.12.21.423514.

Spatial multi-omic map of human myocardial infarction

Kuppe C, Ramirez Flores RO, Li Z, Hannani M, Tanevski J, Halder M, Cheng M, Ziegler S, Zhang X, Preisker F, Kaesler N, Xu Y, Hoogenboezem RM, Bindels EM, Schneider RK, Milting H, Costa IG, Saez-Rodriguez J, Kramann R.

2020

doi:10.1101/2020.12.08.411686.

Reusability and composability in process description maps: RAS-RAF-MEK-ERK signalling

Mazein A, Rougny A, Karr JR, Saez Rodriguez J, Ostaszewski M, Schneider R.

2020

doi:10.1101/2020.12.08.416719.

A statistical framework for assessing pharmacological responses and biomarkers using uncertainty estimates.

Wang D, Hensman J, Kutkaite G, Toh TS, Galhoz A, GDSC Screening Team, Dry JR, Saez-Rodriguez J, Garnett MJ, Menden MP, Dondelinger F.

Elife, 2020

doi:10.7554/elife.60352.

Why do pathway methods work better than they should?

Szalai B, Saez-Rodriguez J.

FEBS Lett, 2020

doi:10.1002/1873-3468.14011.

COVID-19 Disease Map, a computational knowledge repository of SARS-CoV-2 virus-host interaction mechanisms

Ostaszewski M, Niarakis A, Mazein A, Kuperstein I, Phair R, Orta-Resendiz A, Singh V, Aghamiri SS, Acencio ML, Glaab E, Ruepp A, Fobo G, Montrone C, Brauner B, Frishman G, Cristóbal Monraz Gómez L, Somers J, Hoch M, Gupta SK, Scheel J, Borlinghaus H, Czauderna T, Schreiber F, Montagud A, Leon MPd, Funahashi A, Hiki Y, Hiroi N, Yamada TG, Dräger A, Renz A, Naveez M, Bocskei Z, Messina F, Börnigen D, Fergusson L, Conti M, Rameil M, Nakonecnij V, Vanhoefer J, Schmiester L, Wang M, Ackerman EE, Shoemaker J, Zucker J, Oxford K, Teuton J, Kocakaya E, Yağmur Summak G, Hanspers K, Kutmon M, Coort S, Eijssen L, Ehrhart F, Rex DAB, Slenter D, Martens M, Pham N, Haw R, Jassal B, Matthews L, Orlic-Milacic M, Ribeiro AS, Rothfels K, Shamovsky V, Stephan R, Sevilla C, Varusai T, Ravel J, Fraser R, Ortseifen V, Marchesi S, Gawron P, Smula E, Heirendt L, Satagopam V, Wu G, Riutta A, Golebiewski M, Owen S, Goble C, Hu X, Overall RW, Maier D, Bauch A, Gyori BM, Bachman JA, Vega C, Grouès V, Vazquez M, Porras P, Licata L, Iannuccelli M, Sacco F, Nesterova A, Yuryev A, Waard Ad, Turei D, Luna A, Babur O, Soliman S, Valdeolivas A, Medina ME, Peña-Chilet M, Rian K, Helikar T, Puniya BL, Modos D, Treveil A, Olbei M, Meulder BD, Dugourd A, Naldi A, Noë V, Calzone L, Sander C, Demir E, Korcsmaros T, Freeman TC, Augé F, Beckmann JS, Hasenauer J, Wolkenhauer O, Wilighagen EL, Pico AR, Evelo CT, Gillespie ME, Gillespie ME, Stein LD, Hermjakob H, D’Eustachio P, Saez-Rodriguez J, Dopazo J, Valencia A, Kitano H, Barillot E, Auffray C, Balling R, Schneider R, the COVID-19 Disease Map Community.

2020

doi:10.1101/2020.10.26.356014.

Gene selection for optimal prediction of cell position in tissues from single-cell transcriptomics data.

Tanevski J, Nguyen T, Truong B, Karaiskos N, Ahsen ME, Zhang X, Shu C, Xu K, Liang X, Hu Y, Pham HV, Xiaomei L, Le TD, Tarca AL, Bhatti G, Romero R, Karathanasis N, Loher P, Chen Y, Ouyang Z, Mao D, Zhang Y, Zand M, Ruan J, Hafemeister C, Qiu P, Tran D, Nguyen T, Gabor A, Yu T, Guinney J, Glaab E, Krause R, Banda P, DREAM SCTC Consortium, Stolovitzky G, Rajewsky N, Saez-Rodriguez J, Meyer P.

Life Sci Alliance, 2020

doi:10.26508/lsa.202000867.

Only Hyperuricemia with Crystalluria, but not Asymptomatic Hyperuricemia, Drives Progression of Chronic Kidney Disease.

Sellmayr M, Hernandez Petzsche MR, Ma Q, Krüger N, Liapis H, Brink A, Lenz B, Angelotti ML, Gnemmi V, Kuppe C, Kim H, Bindels EMJ, Tajti F, Saez-Rodriguez J, Lech M, Kramann R, Romagnani P, Anders HJ, Steiger S.

J Am Soc Nephrol, 2020

doi:10.1681/asn.2020040523.

Deep spatial profiling of COVID19 brains reveals neuroinflammation by compartmentalized local immune cell interactions and targets for intervention

Bengsch B, Schwabenland M, Salié H, Tanevski J, Killmer S, Matschke J, Püschel K, Mei H, Boettler T, Neumann-Haefelin C, Hofmann M, Saez-Rodriguez J, Knobeloch K, Blank T, Thimme R, Glatzel M, Prinz M.

2020

doi:10.21203/rs.3.rs-63687/v1.

SBML Level 3: an extensible format for the exchange and reuse of biological models.

Keating SM, Waltemath D, König M, Zhang F, Dräger A, Chaouiya C, Bergmann FT, Finney A, Gillespie CS, Helikar T, Hoops S, Malik-Sheriff RS, Moodie SL, Moraru II, Myers CJ, Naldi A, Olivier BG, Sahle S, Schaff JC, Smith LP, Swat MJ, Thieffry D, Watanabe L, Wilkinson DJ, Blinov ML, Begley K, Faeder JR, Gómez HF, Hamm TM, Inagaki Y, Liebermeister W, Lister AL, Lucio D, Mjolsness E, Proctor CJ, Raman K, Rodriguez N, Shaffer CA, Shapiro BE, Stelling J, Swainston N, Tanimura N, Wagner J, Meier-Schellersheim M, Sauro HM, Palsson B, Bolouri H, Kitano H, Funahashi A, Hermjakob H, Doyle JC, Hucka M, SBML Level 3 Community members.

Mol Syst Biol, 2020

doi:10.15252/msb.20199110.

Inferring clonal composition from multiple tumor biopsies.

Manica M, Kim HR, Mathis R, Chouvarine P, Rutishauser D, De Vargas Roditi L, Szalai B, Wagner U, Oehl K, Saba K, Pati A, Saez-Rodriguez J, Roy A, Parsons DW, Wild PJ, Martínez MR, Sumazin P.

NPJ Syst Biol Appl, 2020

doi:10.1038/s41540-020-00147-5.

Big Data Approaches in Heart Failure Research.

Lanzer JD, Leuschner F, Kramann R, Levinson RT, Saez-Rodriguez J.

Curr Heart Fail Rep, 2020

doi:10.1007/s11897-020-00469-9.

Integrated intra- and intercellular signaling knowledge for multicellular omics analysis

Türei D, Valdeolivas A, Gul L, Palacio-Escat N, Ivanova O, Gábor A, Módos D, Korcsmáros T, Saez-Rodriguez J.

2020

doi:10.1101/2020.08.03.221242.

Why do pathway methods work better than they should?

Szalai B, Saez-Rodriguez J.

2020

doi:10.1101/2020.07.30.228296.

Increased CXCL4 expression in hematopoietic cells links inflammation and progression of bone marrow fibrosis in MPN.

Gleitz HFE, Dugourd AJF, Leimkühler NB, Snoeren IAM, Fuchs SNR, Menzel S, Ziegler S, Kröger N, Triviai I, Büsche G, Kreipe H, Banjanin B, Pritchard JE, Hoogenboezem R, Bindels EM, Schumacher N, Rose-John S, Elf S, Saez-Rodriguez J, Kramann R, Schneider RK.

Blood, 2020

doi:10.1182/blood.2019004095.

Community Assessment of the Predictability of Cancer Protein and Phosphoprotein Levels from Genomics and Transcriptomics.

Yang M, Petralia F, Li Z, Li H, Ma W, Song X, Kim S, Lee H, Yu H, Lee B, Bae S, Heo E, Kaczmarczyk J, Stępniak P, Warchoł M, Yu T, Calinawan AP, Boutros PC, Payne SH, Reva B, NCI-CPTAC-DREAM Consortium, Boja E, Rodriguez H, Stolovitzky G, Guan Y, Kang J, Wang P, Fenyö D, Saez-Rodriguez J.

Cell Syst, 2020

doi:10.1016/j.cels.2020.06.013.

DreamAI: algorithm for the imputation of proteomics data

Ma W, Kim S, Chowdhury S, Li Z, Yang M, Yoo S, Petralia F, Jacobsen J, Li JJ, Ge X, Li K, Yu T, Calinawan AP, Edwards N, Payne SH, Boutros PC, Rodriguez H, Stolovitzky G, Zhu J, Kang J, Fenyo D, Saez-Rodriguez J, Wang P.

2020

doi:10.1101/2020.07.21.214205.

A comprehensive and centralized database for exploring omics data in Autoimmune Diseases

Martorell-Marugán J, Lopez-Dominguez R, Garcia-Moreno A, Toro-Dominguez D, Villatoro-Garcia JA, Barturen G, Martin-Gomez A, Troule K, Gomez-Lopez G, Al-Shahrour F, Gonzalez-Rumayor V, Peña-Chilet M, Dopazo J, Saez-Rodriguez J, Alarcon-Riquelme ME, Carmona-Saez P.

2020

doi:10.1101/2020.06.10.144972.

Converting networks to predictive logic models from perturbation signalling data with CellNOpt.

Gjerga E, Trairatphisan P, Gabor A, Koch H, Chevalier C, Ceccarelli F, Dugourd A, Mitsos A, Saez-Rodriguez J.

Bioinformatics, 2020

doi:10.1093/bioinformatics/btaa561.

Stratification and prediction of drug synergy based on target functional similarity.

Yang M, Jaaks P, Dry J, Garnett M, Menden MP, Saez-Rodriguez J.

NPJ Syst Biol Appl, 2020

doi:10.1038/s41540-020-0136-x.

PYCR1-dependent proline synthesis in cancer-associated fibroblasts is required for the deposition of pro-tumorigenic extracellular matrix

Kay EJ, Paterson K, Domingo CR, Sumpton D, Daebritz H, Tardito S, Boldrini C, Hernandez-Fernaud JR, Athineos D, Dhayade S, Stepanova E, Gjerga E, Neilson LJ, Lilla S, Hedley A, Koulouras G, McGregor G, Jamieson C, Johnson RM, Park M, Kirschner K, Kirschner K, Miller C, Kamphorst JJ, Loayza-Puch F, Saez-Rodriguez J, Mazzone M, Blyth K, Zagnoni M, Zanivan S.

2020

doi:10.1101/2020.05.30.125237.

A Consensus Transcriptional Landscape of Human End-Stage Heart Failure

Flores ROR, Lanzer JD, Holland CH, Leuschner F, Most P, Schultz J, Levinson RT, Saez-Rodriguez J.

2020

doi:10.1101/2020.05.23.20110858.

CELLector: Genomics-Guided Selection of Cancer In Vitro Models.

Najgebauer H, Yang M, Francies HE, Pacini C, Stronach EA, Garnett MJ, Saez-Rodriguez J, Iorio F.

Cell Syst, 2020

doi:10.1016/j.cels.2020.04.007.

Explainable multi-view framework for dissecting intercellular signaling from highly multiplexed spatial data

Tanevski J, Flores ROR, Gabor A, Schapiro D, Saez-Rodriguez J.

2020

doi:10.1101/2020.05.08.084145.

A statistical framework for assessing pharmacological response and biomarkers using uncertainty estimates

Wang D, Hensman J, Kutkaite G, Toh TS, Dry JR, Saez-Rodriguez J, Garnett MJ, Menden MP, Dondelinger F, GDSC Screening Team.

2020

doi:10.1101/2020.05.01.072983.

The Minimum Information about a Molecular Interaction Causal Statement (MI2CAST)

Touré V, Vercruysse S, Acencio ML, Lovering R, Orchard S, Bradley G, Casals-Casas C, Chaouiya C, del-Toro N, Flobak Å, Gaudet P, Hermjakob H, Licata L, Lægreid A, Mungall C, Niknejad A, Panni S, Perfetto L, Porras P, Pratt D, Thieffry D, Thomas P, Türei D, Saez-Rodriguez J, Kuiper M.

2020

doi:10.20944/preprints202004.0480.v1.

Causal integration of multi-omics data with prior knowledge to generate mechanistic hypotheses

Dugourd A, Kuppe C, Sciacovelli M, Gjerga E, Emdal KB, Bekker-Jensen DB, Kranz J, Bindels EMJ, Costa ASH, Olsen JV, Frezza C, Kramann R, Saez-Rodriguez J.

2020

doi:10.1101/2020.04.23.057893.

Converting networks to predictive logic models from perturbation signalling data with CellNOpt

Gjerga E, Trairatphisan P, Gabor A, Koch H, Chevalier C, Ceccarelli F, Dugourd A, Mitsos A, Saez-Rodriguez J.

2020

doi:10.1101/2020.03.04.976852.

Personalized signaling models for personalized treatments.

Saez-Rodriguez J, Blüthgen N.

Mol Syst Biol, 2020

doi:10.15252/msb.20199042.

Patient-specific logic models of signaling pathways from screenings on cancer biopsies to prioritize personalized combination therapies.

Eduati F, Jaaks P, Wappler J, Cramer T, Merten CA, Garnett MJ, Saez-Rodriguez J.

Mol Syst Biol, 2020

doi:10.15252/msb.20188664.

Robustness and applicability of transcription factor and pathway analysis tools on single-cell RNA-seq data.

Holland CH, Tanevski J, Perales-Patón J, Gleixner J, Kumar MP, Mereu E, Joughin BA, Stegle O, Lauffenburger DA, Heyn H, Szalai B, Saez-Rodriguez J.

Genome Biol, 2020

doi:10.1186/s13059-020-1949-z.

A Functional Landscape of CKD Entities From Public Transcriptomic Data.

Tajti F, Kuppe C, Antoranz A, Ibrahim MM, Kim H, Ceccarelli F, Holland CH, Olauson H, Floege J, Alexopoulos LG, Kramann R, Saez-Rodriguez J.

Kidney Int Rep, 2020

doi:10.1016/j.ekir.2019.11.005.

Deciphering the Signaling Network Landscape of Breast Cancer Improves Drug Sensitivity Prediction

Tognetti M, Gabor A, Yang M, Cappelletti V, Windhager J, Charmpi K, de Souza N, Beyer A, Picotti P, Saez-Rodriguez J, Bodenmiller B.

2020

doi:10.1101/2020.01.21.907691.

Dysregulated mesenchymal PDGFR-β drives kidney fibrosis.

Buhl EM, Djudjaj S, Klinkhammer BM, Ermert K, Puelles VG, Lindenmeyer MT, Cohen CD, He C, Borkham-Kamphorst E, Weiskirchen R, Denecke B, Trairatphisan P, Saez-Rodriguez J, Huber TB, Olson LE, Floege J, Boor P.

EMBO Mol Med, 2020

doi:10.15252/emmm.201911021.

Quantitative Systems Toxicology Modeling To Address Key Safety Questions in Drug Development: A Focus of the TransQST Consortium.

Ferreira S, Fisher C, Furlong LI, Laplanche L, Park BK, Pin C, Saez-Rodriguez J, Trairatphisan P.

Chem Res Toxicol, 2020

doi:10.1021/acs.chemrestox.9b00499.

Bringing data from curated pathway resources to Cytoscape with OmniPath.

Ceccarelli F, Turei D, Gabor A, Saez-Rodriguez J.

Bioinformatics, 2020

doi:10.1093/bioinformatics/btz968.

Kinetic modelling of quantitative proteome data predicts metabolic reprogramming of liver cancer.

Berndt N, Egners A, Mastrobuoni G, Vvedenskaya O, Fragoulis A, Dugourd A, Bulik S, Pietzke M, Bielow C, van Gassel R, Damink SWO, Erdem M, Saez-Rodriguez J, Holzhütter HG, Kempa S, Cramer T.

Br J Cancer, 2020

doi:10.1038/s41416-019-0659-3.

Transfer of regulatory knowledge from human to mouse for functional genomics analysis.

Holland CH, Szalai B, Saez-Rodriguez J.

Biochim Biophys Acta Gene Regul Mech, 2020

doi:10.1016/j.bbagrm.2019.194431.

Footprint-based functional analysis of multiomic data.

Dugourd A, Saez-Rodriguez J.

Curr Opin Syst Biol, 2019

doi:10.1016/j.coisb.2019.04.002.

Metabolic rewiring of the hypertensive kidney.

Rinschen MM, Palygin O, Guijas C, Palermo A, Palacio-Escat N, Domingo-Almenara X, Montenegro-Burke R, Saez-Rodriguez J, Staruschenko A, Siuzdak G.

Sci Signal, 2019

doi:10.1126/scisignal.aax9760.

Influence of Liver Fibrosis on Lobular Zonation.

Ghallab A, Myllys M, Holland CH, Zaza A, Murad W, Hassan R, Ahmed YA, Abbas T, Abdelrahim EA, Schneider KM, Matz-Soja M, Reinders J, Gebhardt R, Berres ML, Hatting M, Drasdo D, Saez-Rodriguez J, Trautwein C, Hengstler JG.

Cells, 2019

doi:10.3390/cells8121556.

The authors reply.

Saez-Rodriguez J, Rinschen MM, Floege J, Kramann R.

Kidney Int, 2019

doi:10.1016/j.kint.2019.09.011.

Quantitative Proteome Landscape of the NCI-60 Cancer Cell Lines.

Guo T, Luna A, Rajapakse VN, Koh CC, Wu Z, Liu W, Sun Y, Gao H, Menden MP, Xu C, Calzone L, Martignetti L, Auwerx C, Buljan M, Banaei-Esfahani A, Ori A, Iskar M, Gillet L, Bi R, Zhang J, Zhang H, Yu C, Zhong Q, Varma S, Schmitt U, Qiu P, Zhang Q, Zhu Y, Wild PJ, Garnett MJ, Bork P, Beck M, Liu K, Saez-Rodriguez J, Elloumi F, Reinhold WC, Sander C, Pommier Y, Aebersold R.

iScience, 2019

doi:10.1016/j.isci.2019.10.059.

From expression footprints to causal pathways: contextualizing large signaling networks with CARNIVAL.

Liu A, Trairatphisan P, Gjerga E, Didangelos A, Barratt J, Saez-Rodriguez J.

NPJ Syst Biol Appl, 2019

doi:10.1038/s41540-019-0118-z.

Toward Explainable Anticancer Compound Sensitivity Prediction via Multimodal Attention-Based Convolutional Encoders.

Manica M, Oskooei A, Born J, Subramanian V, Sáez-Rodríguez J, Rodríguez Martínez M.

Mol Pharm, 2019

doi:10.1021/acs.molpharmaceut.9b00520.

Predicting cellular position in the <i>Drosophila</i> embryo from Single-Cell Transcriptomics data

Tanevski J, Nguyen T, Truong B, Karaiskos N, Ahsen ME, Zhang X, Shu C, Xu K, Liang X, Hu Y, Pham HV, Xiaomei L, Le TD, Tarca AL, Bhatti G, Romero R, Karathanasis N, Loher P, Chen Y, Ouyang Z, Mao D, Zhang Y, Zand M, Ruan J, Hafemeister C, Qiu P, Tran D, Nguyen T, Gabor A, Yu T, Glaab E, Krause R, Banda P, Stolovitzky G, Rajewsky N, Saez-Rodriguez J, Meyer P, DREAM SCTC Consortium.

2019

doi:10.1101/796029.

Modeling Cell-Cell Interactions from Spatial Molecular Data with Spatial Variance Component Analysis.

Arnol D, Schapiro D, Bodenmiller B, Saez-Rodriguez J, Stegle O.

Cell Rep, 2019

doi:10.1016/j.celrep.2019.08.077.

Signatures of cell death and proliferation in perturbation transcriptomics data-from confounding factor to effective prediction.

Szalai B, Subramanian V, Holland CH, Alföldi R, Puskás LG, Saez-Rodriguez J.

Nucleic Acids Res, 2019

doi:10.1093/nar/gkz805.

Reproducible biomedical benchmarking in the cloud: lessons from crowd-sourced data challenges.

Ellrott K, Buchanan A, Creason A, Mason M, Schaffter T, Hoff B, Eddy J, Chilton JM, Yu T, Stuart JM, Saez-Rodriguez J, Stolovitzky G, Boutros PC, Guinney J.

Genome Biol, 2019

doi:10.1186/s13059-019-1794-0.

Robustness and applicability of functional genomics tools on scRNA-seq data

Holland CH, Tanevski J, Gleixner J, Kumar MP, Mereu E, Perales-Patón J, Joughin BA, Stegle O, Lauffenburger DA, Heyn H, Szalai B, Saez-Rodriguez J.

2019

doi:10.1101/753319.

Assessment of network module identification across complex diseases.

Choobdar S, Ahsen ME, Crawford J, Tomasoni M, Fang T, Lamparter D, Lin J, Hescott B, Hu X, Mercer J, Natoli T, Narayan R, DREAM Module Identification Challenge Consortium, Subramanian A, Zhang JD, Stolovitzky G, Kutalik Z, Lage K, Slonim DK, Saez-Rodriguez J, Cowen LJ, Bergmann S, Marbach D.

Nat Methods, 2019

doi:10.1038/s41592-019-0509-5.

Elucidating essential kinases of endothelin signalling by logic modelling of phosphoproteomics data.

Schäfer A, Gjerga E, Welford RW, Renz I, Lehembre F, Groenen PM, Saez-Rodriguez J, Aebersold R, Gstaiger M.

Mol Syst Biol, 2019

doi:10.15252/msb.20198828.

Novel plasma peptide markers involved in the pathology of CKD identified using mass spectrometric approach.

Gajjala PR, Bruck H, Noels H, Heinze G, Ceccarelli F, Kribben A, Saez-Rodriguez J, Marx N, Zidek W, Jankowski J, Jankowski V.

J Mol Med (Berl), 2019

doi:10.1007/s00109-019-01823-8.

Benchmark and integration of resources for the estimation of human transcription factor activities.

Garcia-Alonso L, Holland CH, Ibrahim MM, Turei D, Saez-Rodriguez J.

Genome Res, 2019

doi:10.1101/gr.240663.118.

Network pharmacology modeling identifies synergistic Aurora B and ZAK interaction in triple-negative breast cancer.

Tang J, Gautam P, Gupta A, He L, Timonen S, Akimov Y, Wang W, Szwajda A, Jaiswal A, Turei D, Yadav B, Kankainen M, Saarela J, Saez-Rodriguez J, Wennerberg K, Aittokallio T.

NPJ Syst Biol Appl, 2019

doi:10.1038/s41540-019-0098-z.

Community assessment to advance computational prediction of cancer drug combinations in a pharmacogenomic screen.

Menden MP, Wang D, Mason MJ, Szalai B, Bulusu KC, Guan Y, Yu T, Kang J, Jeon M, Wolfinger R, Nguyen T, Zaslavskiy M, AstraZeneca-Sanger Drug Combination DREAM Consortium, Jang IS, Ghazoui Z, Ahsen ME, Vogel R, Neto EC, Norman T, Tang EKY, Garnett MJ, Veroli GYD, Fawell S, Stolovitzky G, Guinney J, Dry JR, Saez-Rodriguez J.

Nat Commun, 2019

doi:10.1038/s41467-019-09799-2.

Analysis of the Human Kinome and Phosphatome by Mass Cytometry Reveals Overexpression-Induced Effects on Cancer-Related Signaling.

Lun XK, Szklarczyk D, Gábor A, Dobberstein N, Zanotelli VRT, Saez-Rodriguez J, von Mering C, Bodenmiller B.

Mol Cell, 2019

doi:10.1016/j.molcel.2019.04.021.

Functional linkage of gene fusions to cancer cell fitness assessed by pharmacological and CRISPR-Cas9 screening.

Picco G, Chen ED, Alonso LG, Behan FM, Gonçalves E, Bignell G, Matchan A, Fu B, Banerjee R, Anderson E, Butler A, Benes CH, McDermott U, Dow D, Iorio F, Stronach E, Yang F, Yusa K, Saez-Rodriguez J, Garnett MJ.

Nat Commun, 2019

doi:10.1038/s41467-019-09940-1.

Author Correction: Linking drug target and pathway activation for effective therapy using multi-task learning.

Yang M, Simm J, Lam CC, Zakeri P, van Westen GJP, Moreau Y, Saez-Rodriguez J.

Sci Rep, 2019

doi:10.1038/s41598-019-43503-0.

MEK1/2 inhibitor withdrawal reverses acquired resistance driven by BRAF<sup>V600E</sup> amplification whereas KRAS<sup>G13D</sup> amplification promotes EMT-chemoresistance.

Sale MJ, Balmanno K, Saxena J, Ozono E, Wojdyla K, McIntyre RE, Gilley R, Woroniuk A, Howarth KD, Hughes G, Dry JR, Arends MJ, Caro P, Oxley D, Ashton S, Adams DJ, Saez-Rodriguez J, Smith PD, Cook SJ.

Nat Commun, 2019

doi:10.1038/s41467-019-09438-w.

MAPK pathway and B cells overactivation in multiple sclerosis revealed by phosphoproteomics and genomic analysis.

Kotelnikova E, Kiani NA, Messinis D, Pertsovskaya I, Pliaka V, Bernardo-Faura M, Rinas M, Vila G, Zubizarreta I, Pulido-Valdeolivas I, Sakellaropoulos T, Faigle W, Silberberg G, Masso M, Stridh P, Behrens J, Olsson T, Martin R, Paul F, Alexopoulos LG, Saez-Rodriguez J, Tegner J, Villoslada P.

Proc Natl Acad Sci U S A, 2019

doi:10.1073/pnas.1818347116.

Big science and big data in nephrology.

Saez-Rodriguez J, Rinschen MM, Floege J, Kramann R.

Kidney Int, 2019

doi:10.1016/j.kint.2018.11.048.

Prioritization of cancer therapeutic targets using CRISPR-Cas9 screens.

Behan FM, Iorio F, Picco G, Gonçalves E, Beaver CM, Migliardi G, Santos R, Rao Y, Sassi F, Pinnelli M, Ansari R, Harper S, Jackson DA, McRae R, Pooley R, Wilkinson P, van der Meer D, Dow D, Buser-Doepner C, Bertotti A, Trusolino L, Stronach EA, Saez-Rodriguez J, Yusa K, Garnett MJ.

Nature, 2019

doi:10.1038/s41586-019-1103-9.

Elastin imaging enables noninvasive staging and treatment monitoring of kidney fibrosis.

Sun Q, Baues M, Klinkhammer BM, Ehling J, Djudjaj S, Drude NI, Daniel C, Amann K, Kramann R, Kim H, Saez-Rodriguez J, Weiskirchen R, Onthank DC, Botnar RM, Kiessling F, Floege J, Lammers T, Boor P.

Sci Transl Med, 2019

doi:10.1126/scitranslmed.aat4865.

Stratification and prediction of drug synergy based on target functional similarity

Yang M, Menden MP, Jaaks P, Dry J, Garnett M, Saez-Rodriguez J.

2019

doi:10.1101/586123.

Functional linkage of gene fusions to cancer cell fitness assessed by pharmacological and CRISPR/Cas9 screening

Picco G, Chen ED, Alonso LG, Behan FM, Gonçalves E, Bignell G, Matchan A, Fu B, Banerjee R, Anderson E, Butler A, Benes CH, McDermott U, Dow D, Iorio F, Stronach E, Yang F, Yusa K, Saez-Rodriguez J, Garnett MJ.

2019

doi:10.1101/559690.

Multi-omic measurements of heterogeneity in HeLa cells across laboratories.

Liu Y, Mi Y, Mueller T, Kreibich S, Williams EG, Van Drogen A, Borel C, Frank M, Germain PL, Bludau I, Mehnert M, Seifert M, Emmenlauer M, Sorg I, Bezrukov F, Bena FS, Zhou H, Dehio C, Testa G, Saez-Rodriguez J, Antonarakis SE, Hardt WD, Aebersold R.

Nat Biotechnol, 2019

doi:10.1038/s41587-019-0037-y.

Prediction of combination therapies based on topological modeling of the immune signaling network in Multiple Sclerosis

Bernardo-Faura M, Rinas M, Wirbel J, Pertsovskaya I, Pliaka V, Messinis DE, Vila G, Sakellaropoulos T, Faigle W, Stridh P, Behrens JR, Olsson T, Martin R, Paul F, Alexopoulos LG, Villoslada P, Saez-Rodriguez J.

2019

doi:10.1101/541458.

From expression footprints to causal pathways: contextualizing large signaling networks with CARNIVAL

Liu A, Trairatphisan P, Gjerga E, Didangelos A, Barratt J, Saez-Rodriguez J.

2019

doi:10.1101/541888.

Transfer of regulatory knowledge from human to mouse for functional genomic analysis

Holland CH, Szalai B, Saez-Rodriguez J.

2019

doi:10.1101/532739.

The proteome microenvironment determines the protective effect of preconditioning in cisplatin-induced acute kidney injury.

Späth MR, Bartram MP, Palacio-Escat N, Hoyer KJR, Debes C, Demir F, Schroeter CB, Mandel AM, Grundmann F, Ciarimboli G, Beyer A, Kizhakkedathu JN, Brodesser S, Göbel H, Becker JU, Benzing T, Schermer B, Höhne M, Burst V, Saez-Rodriguez J, Huesgen PF, Müller RU, Rinschen MM.

Kidney Int, 2019

doi:10.1016/j.kint.2018.08.037.

How to find the right drug for each patient? Advances and challenges in pharmacogenomics.

Kalamara A, Tobalina L, Saez-Rodriguez J.

Curr Opin Syst Biol, 2018

doi:10.1016/j.coisb.2018.07.001.

Embracing the Dark Side: Computational Approaches to Unveil the Functionality of Genes Lacking Biological Annotation in Drug-Induced Liver Injury.

Souza T, Trairatphisan P, Piñero J, Furlong LI, Saez-Rodriguez J, Kleinjans J, Jennen D.

Front Genet, 2018

doi:10.3389/fgene.2018.00527.

Adipocyte-secreted BMP8b mediates adrenergic-induced remodeling of the neuro-vascular network in adipose tissue.

Pellegrinelli V, Peirce VJ, Howard L, Virtue S, Türei D, Senzacqua M, Frontini A, Dalley JW, Horton AR, Bidault G, Severi I, Whittle A, Rahmouni K, Saez-Rodriguez J, Cinti S, Davies AM, Vidal-Puig A.

Nat Commun, 2018

doi:10.1038/s41467-018-07453-x.

Computational discovery of dynamic cell line specific Boolean networks from multiplex time-course data.

Razzaq M, Paulevé L, Siegel A, Saez-Rodriguez J, Bourdon J, Guziolowski C.

PLoS Comput Biol, 2018

doi:10.1371/journal.pcbi.1006538.

Signatures of cell death and proliferation in perturbation transcriptomics data - from confounding factor to effective prediction

Szalai B, Subramanian V, Alföldi R, Puskás LG, Saez-Rodriguez J.

2018

doi:10.1101/454348.

<i>In silico</i> Prioritization of Transporter-Drug Relationships From Drug Sensitivity Screens.

César-Razquin A, Girardi E, Yang M, Brehme M, Saez-Rodriguez J, Superti-Furga G.

Front Pharmacol, 2018

doi:10.3389/fphar.2018.01011.

Patient-specific logic models of signaling pathways from screenings on cancer biopsies to prioritize personalized combination therapies

Eduati F, Jaaks P, Merten CA, Garnett MJ, Rodriguez JS.

2018

doi:10.1101/422998.

The germline genetic component of drug sensitivity in cancer cell lines.

Menden MP, Casale FP, Stephan J, Bignell GR, Iorio F, McDermott U, Garnett MJ, Saez-Rodriguez J, Stegle O.

Nat Commun, 2018

doi:10.1038/s41467-018-05811-3.

Unsupervised correction of gene-independent cell responses to CRISPR-Cas9 targeting.

Iorio F, Behan FM, Gonçalves E, Bhosle SG, Chen E, Shepherd R, Beaver C, Ansari R, Pooley R, Wilkinson P, Harper S, Butler AP, Stronach EA, Saez-Rodriguez J, Yusa K, Garnett MJ.

BMC Genomics, 2018

doi:10.1186/s12864-018-4989-y.

Gli1<sup>+</sup> Mesenchymal Stromal Cells Are a Key Driver of Bone Marrow Fibrosis and an Important Cellular Therapeutic Target.

Schneider RK, Mullally A, Dugourd A, Peisker F, Hoogenboezem R, Van Strien PMH, Bindels EM, Heckl D, Büsche G, Fleck D, Müller-Newen G, Wongboonsin J, Ventura Ferreira M, Puelles VG, Saez-Rodriguez J, Ebert BL, Humphreys BD, Kramann R.

Cell Stem Cell, 2018

doi:10.1016/j.stem.2018.07.006.

A functional landscape of chronic kidney disease entities from public transcriptomic data

Tajti F, Kuppe C, Antoranz A, Ibrahim MM, Kim H, Ceccarelli F, Holland C, Olauson H, Floege J, Alexopoulos LG, Kramann R, Saez-Rodriguez J.

2018

doi:10.1101/265447.

Open Community Challenge Reveals Molecular Network Modules with Key Roles in Diseases

Choobdar S, Ahsen ME, Crawford J, Tomasoni M, Fang T, Lamparter D, Lin J, Hescott B, Hu X, Mercer J, Natoli T, Narayan R, Subramanian A, Zhang JD, Stolovitzky G, Kutalik Z, Lage K, Slonim DK, Saez-Rodriguez J, Cowen LJ, Bergmann S, Marbach D, Aicheler F, Amoroso N, Arenas A, Azhagesan K, Baker A, Banf M, Batzoglou S, Baudot A, Bellotti R, Bergmann S, Boroevich KA, Brun C, Cai S, Caldera M, Calderone A, Cesareni G, Chen W, Chichester C, Choobdar S, Cowen L, Crawford J, Cui H, Dao P, Domenico MD, Dhroso A, Didier G, Divine M, Sol Ad, Fang T, Feng X, Flores-Canales JC, Fortunato S, Gitter A, Gorska A, Guan Y, Guénoche A, Gómez S, Hamza H, Hartmann A, He S, Heijs A, Heinrich J, Hescott B, Hu X, Hu Y, Huang X, Hughitt VK, Jeon M, Jeub L, Johnson N, Joo K, Joung I, Jung S, Kalko SG, Kamola PJ, Kang J, Kaveelerdpotjana B, Kim M, Kim Y, Kohlbacher O, Korkin D, Krzysztof K, Kunji K, Kutalik Z, Lage K, Lamparter D, Lang-Brown S, Le TD, Lee J, Lee S, Lee J, Li D, Li J, Lin J, Liu L, Loizou A, Luo Z, Lysenko A, Ma T, Mall R, Marbach D, Mattia T, Medvedovic M, Menche J, Mercer J, Micarelli E, Monaco A, Müller F, Narayan R, Narykov O, Natoli T, Norman T, Park S, Perfetto L, Perrin D, Pirrò S, Przytycka TM, Qian X, Raman K, Ramazzotti D, Ramsahai E, Ravindran B, Rennert P, Saez-Rodriguez J, Schärfe C, Sharan R, Shi N, Shin W, Shu H, Sinha H, Slonim DK, Spinelli L, Srinivasan S, Subramanian A, Suver C, Szklarczyk D, Tangaro S, Thiagarajan S, Tichit L, Tiede T, Tripathi B, Tsherniak A, Tsunoda T, Türei D, Ullah E, Vahedi G, Valdeolivas A, Vivek J, Mering Cv, Waagmeester A, Wang B, Wang Y, Weir BA, White S, Winkler S, Xu K, Xu T, Yan C, Yang L, Yu K, Yu X, Zaffaroni G, Zaslavskiy M, Zeng T, Zhang JD, Zhang L, Zhang W, Zhang L, Zhang X, Zhang J, Zhou X, Zhou J, Zhu H, Zhu J, Zuccon G, The DREAM Module Identification Challenge Consortium.

2018

doi:10.1101/265553.

Rapid proteotyping reveals cancer biology and drug response determinants in the NCI-60 cells

Guo T, Luna A, Rajapakse VN, Koh CC, Wu Z, Menden MP, Cheng Y, Calzone L, Martignetti L, Ori A, Iskar M, Gillet L, Zhong Q, Varma S, Schmitt U, Qiu P, Sun Y, Zhu Y, Wild PJ, Garnett MJ, Bork P, Beck M, Saez-Rodriguez J, Reinhold WC, Sander C, Pommier Y, Aebersold R.

2018

doi:10.1101/268953.

Kinetic modelling of quantitative proteome data predicts metabolic reprogramming of liver cancer

Berndt N, Egners A, Mastrobuoni G, Vvedenskaya O, Fragoulis A, Dugourd A, Bulik S, Pietzke M, Bielow C, Gassel Rv, Damink SO, Erdem M, Saez-Rodriguez J, Holzhütter H, Kempa S, Cramer T.

2018

doi:10.1101/275040.

Modelling cell-cell interactions from spatial molecular data with spatial variance component analysis

Arnol D, Schapiro D, Bodenmiller B, Saez-Rodriguez J, Stegle O.

2018

doi:10.1101/265256.

CELLector: Genomics Guided Selection of Cancer in vitro Models

Najgebauer H, Yang M, Francies HE, Pacini C, Stronach EA, Garnett MJ, Saez-Rodriguez J, Iorio F.

2018

doi:10.1101/275032.

Analysis of the human kinome and phosphatome reveals diseased signaling networks induced by overexpression

Lun X, Szklarczyk D, Gábor A, Dobberstein N, Zanotelli VR, Saez-Rodriguez J, von Mering C, Bodenmiller B.

2018

doi:10.1101/314716.

Benchmark and integration of resources for the estimation of human transcription factor activities

Garcia-Alonso L, Ibrahim MM, Turei D, Saez-Rodriguez J.

2018

doi:10.1101/337915.

A microfluidics platform for combinatorial drug screening on cancer biopsies.

Eduati F, Utharala R, Madhavan D, Neumann UP, Longerich T, Cramer T, Saez-Rodriguez J, Merten CA.

Nat Commun, 2018

doi:10.1038/s41467-018-04919-w.

Linking drug target and pathway activation for effective therapy using multi-task learning.

Yang M, Simm J, Lam CC, Zakeri P, van Westen GJP, Moreau Y, Saez-Rodriguez J.

Sci Rep, 2018

doi:10.1038/s41598-018-25947-y.

Alternative models for sharing confidential biomedical data.

Guinney J, Saez-Rodriguez J.

Nat Biotechnol, 2018

doi:10.1038/nbt.4128.

Pathway-based dissection of the genomic heterogeneity of cancer hallmarks' acquisition with SLAPenrich.

Iorio F, Garcia-Alonso L, Brammeld JS, Martincorena I, Wille DR, McDermott U, Saez-Rodriguez J.

Sci Rep, 2018

doi:10.1038/s41598-018-25076-6.

Whither systems medicine?

Apweiler R, Beissbarth T, Berthold MR, Blüthgen N, Burmeister Y, Dammann O, Deutsch A, Feuerhake F, Franke A, Hasenauer J, Hoffmann S, Höfer T, Jansen PL, Kaderali L, Klingmüller U, Koch I, Kohlbacher O, Kuepfer L, Lammert F, Maier D, Pfeifer N, Radde N, Rehm M, Roeder I, Saez-Rodriguez J, Sax U, Schmeck B, Schuppert A, Seilheimer B, Theis FJ, Vera J, Wolkenhauer O.

Exp Mol Med, 2018

doi:10.1038/emm.2017.290.

NADH Shuttling Couples Cytosolic Reductive Carboxylation of Glutamine with Glycolysis in Cells with Mitochondrial Dysfunction.

Gaude E, Schmidt C, Gammage PA, Dugourd A, Blacker T, Chew SP, Saez-Rodriguez J, O'Neill JS, Szabadkai G, Minczuk M, Frezza C.

Mol Cell, 2018

doi:10.1016/j.molcel.2018.01.034.

Phosphoproteomics-Based Profiling of Kinase Activities in Cancer Cells.

Wirbel J, Cutillas P, Saez-Rodriguez J.

Methods Mol Biol, 2018

doi:10.1007/978-1-4939-7493-1_6.

Perturbation-response genes reveal signaling footprints in cancer gene expression.

Schubert M, Klinger B, Klünemann M, Sieber A, Uhlitz F, Sauer S, Garnett MJ, Blüthgen N, Saez-Rodriguez J.

Nat Commun, 2018

doi:10.1038/s41467-017-02391-6.

A systematic atlas of chaperome deregulation topologies across the human cancer landscape.

Hadizadeh Esfahani A, Sverchkova A, Saez-Rodriguez J, Schuppert AA, Brehme M.

PLoS Comput Biol, 2018

doi:10.1371/journal.pcbi.1005890.

Transcription Factor Activities Enhance Markers of Drug Sensitivity in Cancer.

Garcia-Alonso L, Iorio F, Matchan A, Fonseca N, Jaaks P, Peat G, Pignatelli M, Falcone F, Benes CH, Dunham I, Bignell G, McDade SS, Garnett MJ, Saez-Rodriguez J.

Cancer Res, 2018

doi:10.1158/0008-5472.can-17-1679.

Post-translational regulation of metabolism in fumarate hydratase deficient cancer cells.

Gonçalves E, Sciacovelli M, Costa ASH, Tran MGB, Johnson TI, Machado D, Frezza C, Saez-Rodriguez J.

Metab Eng, 2018

doi:10.1016/j.ymben.2017.11.011.

GDSCTools for mining pharmacogenomic interactions in cancer.

Cokelaer T, Chen E, Iorio F, Menden MP, Lightfoot H, Saez-Rodriguez J, Garnett MJ.

Bioinformatics, 2018

doi:10.1093/bioinformatics/btx744.

Post-translational regulation of metabolism in fumarate hydratase deficient cancer cells

Gonçalves E, Sciacovelli M, Costa ASH, Isaac Johnson T, Machado D, Frezza C, Saez-Rodriguez J.

2017

doi:10.1101/149716.

A cancer pharmacogenomic screen powering crowd-sourced advancement of drug combination prediction

Menden MP, Wang D, Guan Y, Mason MJ, Szalai B, Bulusu KC, Yu T, Kang J, Jeon M, Wolfinger R, Nguyen T, Zaslavskiy M, Jang S, Ghazoui Z, Ahsen ME, Vogel R, Neto EC, Norman T, Tang EK, Garnett MJ, Di Veroli G, Fawell S, Stolovitzky G, Guinney J, Dry JR, Saez-Rodriguez J, AstraZeneca-Sanger Drug Combination DREAM Consortium.

2017

doi:10.1101/200451.

Unsupervised correction of gene-independent cell responses to CRISPR-Cas9 targeting

Iorio F, Behan FM, Gonçalves E, Bhosle SG, Chen E, Shepherd R, Beaver C, Ansari R, Pooley R, Wilkinson P, Harper S, Butler AP, Stronach EA, Saez-Rodriguez J, Yusa K, Garnett MJ.

2017

doi:10.1101/228189.

Systems Pharmacology Dissection of Cholesterol Regulation Reveals Determinants of Large Pharmacodynamic Variability between Cell Lines.

Blattmann P, Henriques D, Zimmermann M, Frommelt F, Sauer U, Saez-Rodriguez J, Aebersold R.

Cell Syst, 2017

doi:10.1016/j.cels.2017.11.002.

Widespread Post-transcriptional Attenuation of Genomic Copy-Number Variation in Cancer.

Gonçalves E, Fragoulis A, Garcia-Alonso L, Cramer T, Saez-Rodriguez J, Beltrao P.

Cell Syst, 2017

doi:10.1016/j.cels.2017.08.013.

A Community Challenge for Inferring Genetic Predictors of Gene Essentialities through Analysis of a Functional Screen of Cancer Cell Lines.

Gönen M, Weir BA, Cowley GS, Vazquez F, Guan Y, Jaiswal A, Karasuyama M, Uzunangelov V, Wang T, Tsherniak A, Howell S, Marbach D, Hoff B, Norman TC, Airola A, Bivol A, Bunte K, Carlin D, Chopra S, Deran A, Ellrott K, Gopalacharyulu P, Graim K, Kaski S, Khan SA, Newton Y, Ng S, Pahikkala T, Paull E, Sokolov A, Tang H, Tang J, Wennerberg K, Xie Y, Zhan X, Zhu F, Broad-DREAM Community, Aittokallio T, Mamitsuka H, Stuart JM, Boehm JS, Root DE, Xiao G, Stolovitzky G, Hahn WC, Margolin AA.

Cell Syst, 2017

doi:10.1016/j.cels.2017.09.004.

Genomic Determinants of Protein Abundance Variation in Colorectal Cancer Cells.

Roumeliotis TI, Williams SP, Gonçalves E, Alsinet C, Del Castillo Velasco-Herrera M, Aben N, Ghavidel FZ, Michaut M, Schubert M, Price S, Wright JC, Yu L, Yang M, Dienstmann R, Guinney J, Beltrao P, Brazma A, Pardo M, Stegle O, Adams DJ, Wessels L, Saez-Rodriguez J, McDermott U, Choudhary JS.

Cell Rep, 2017

doi:10.1016/j.celrep.2017.08.010.

A parallel metaheuristic for large mixed-integer dynamic optimization problems, with applications in computational biology.

Penas DR, Henriques D, González P, Doallo R, Saez-Rodriguez J, Banga JR.

PLoS One, 2017

doi:10.1371/journal.pone.0182186.

GDSCTools for Mining Pharmacogenomic Interactions in Cancer

Cokelaer T, Chen E, Iorio F, Menden MP, Lightfoot H, Saez-Rodriguez J, Garnett MJ.

2017

doi:10.1101/166223.

Logic Modeling in Quantitative Systems Pharmacology.

Traynard P, Tobalina L, Eduati F, Calzone L, Saez-Rodriguez J.

CPT Pharmacometrics Syst Pharmacol, 2017

doi:10.1002/psp4.12225.

Transcription factor activities enhance markers of drug response in cancer

Garcia-Alonso L, Iorio F, Matchan A, Fonseca N, Jaaks P, Falcone F, Bignell G, McDade SS, Garnett MJ, Saez-Rodriguez J.

2017

doi:10.1101/129478.

Mechanism-based biomarker discovery.

Antoranz A, Sakellaropoulos T, Saez-Rodriguez J, Alexopoulos LG.

Drug Discov Today, 2017

doi:10.1016/j.drudis.2017.04.013.

Gli1<sup>+</sup> Mesenchymal Stromal Cells Are a Key Driver of Bone Marrow Fibrosis and an Important Cellular Therapeutic Target.

Schneider RK, Mullally A, Dugourd A, Peisker F, Hoogenboezem R, Van Strien PMH, Bindels EM, Heckl D, Büsche G, Fleck D, Müller-Newen G, Wongboonsin J, Ventura Ferreira M, Puelles VG, Saez-Rodriguez J, Ebert BL, Humphreys BD, Kramann R.

Cell Stem Cell, 2017

doi:10.1016/j.stem.2017.03.008.

Drug Resistance Mechanisms in Colorectal Cancer Dissected with Cell Type-Specific Dynamic Logic Models.

Eduati F, Doldàn-Martelli V, Klinger B, Cokelaer T, Sieber A, Kogera F, Dorel M, Garnett MJ, Blüthgen N, Saez-Rodriguez J.

Cancer Res, 2017

doi:10.1158/0008-5472.can-17-0078.

Benchmarking substrate-based kinase activity inference using phosphoproteomic data.

Hernandez-Armenta C, Ochoa D, Gonçalves E, Saez-Rodriguez J, Beltrao P.

Bioinformatics, 2017

doi:10.1093/bioinformatics/btx082.

Genome-wide chemical mutagenesis screens allow unbiased saturation of the cancer genome and identification of drug resistance mutations.

Brammeld JS, Petljak M, Martincorena I, Williams SP, Alonso LG, Dalmases A, Bellosillo B, Robles-Espinoza CD, Price S, Barthorpe S, Tarpey P, Alifrangis C, Bignell G, Vidal J, Young J, Stebbings L, Beal K, Stratton MR, Saez-Rodriguez J, Garnett M, Montagut C, Iorio F, McDermott U.

Genome Res, 2017

doi:10.1101/gr.213546.116.

Data-driven reverse engineering of signaling pathways using ensembles of dynamic models.

Henriques D, Villaverde AF, Rocha M, Saez-Rodriguez J, Banga JR.

PLoS Comput Biol, 2017

doi:10.1371/journal.pcbi.1005379.

Systematic Analysis of Transcriptional and Post-transcriptional Regulation of Metabolism in Yeast.

Gonçalves E, Raguz Nakic Z, Zampieri M, Wagih O, Ochoa D, Sauer U, Beltrao P, Saez-Rodriguez J.

PLoS Comput Biol, 2017

doi:10.1371/journal.pcbi.1005297.

caspo: a toolbox for automated reasoning on the response of logical signaling networks families.

Videla S, Saez-Rodriguez J, Guziolowski C, Siegel A.

Bioinformatics, 2017

doi:10.1093/bioinformatics/btw738.

Stem cell-like transcriptional reprogramming mediates metastatic resistance to mTOR inhibition.

Mateo F, Arenas EJ, Aguilar H, Serra-Musach J, de Garibay GR, Boni J, Maicas M, Du S, Iorio F, Herranz-Ors C, Islam A, Prado X, Llorente A, Petit A, Vidal A, Català I, Soler T, Venturas G, Rojo-Sebastian A, Serra H, Cuadras D, Blanco I, Lozano J, Canals F, Sieuwerts AM, de Weerd V, Look MP, Puertas S, García N, Perkins AS, Bonifaci N, Skowron M, Gómez-Baldó L, Hernández V, Martínez-Aranda A, Martínez-Iniesta M, Serrat X, Cerón J, Brunet J, Barretina MP, Gil M, Falo C, Fernández A, Morilla I, Pernas S, Plà MJ, Andreu X, Seguí MA, Ballester R, Castellà E, Nellist M, Morales S, Valls J, Velasco A, Matias-Guiu X, Figueras A, Sánchez-Mut JV, Sánchez-Céspedes M, Cordero A, Gómez-Miragaya J, Palomero L, Gómez A, Gajewski TF, Cohen EEW, Jesiotr M, Bodnar L, Quintela-Fandino M, López-Bigas N, Valdés-Mas R, Puente XS, Viñals F, Casanovas O, Graupera M, Hernández-Losa J, Ramón Y Cajal S, García-Alonso L, Saez-Rodriguez J, Esteller M, Sierra A, Martín-Martín N, Matheu A, Carracedo A, González-Suárez E, Nanjundan M, Cortés J, Lázaro C, Odero MD, Martens JWM, Moreno-Bueno G, Barcellos-Hoff MH, Villanueva A, Gomis RR, Pujana MA.

Oncogene, 2017

doi:10.1038/onc.2016.427.

System-Wide Quantitative Proteomics of the Metabolic Syndrome in Mice: Genotypic and Dietary Effects.

Terfve C, Sabidó E, Wu Y, Gonçalves E, Choi M, Vaga S, Vitek O, Saez-Rodriguez J, Aebersold R.

J Proteome Res, 2017

doi:10.1021/acs.jproteome.6b00815.

System-wide quantitative proteomics of the metabolic syndrome in mice: genotypic and dietary effects

Terfve C, Sabidó E, Wu Y, Gonçalves E, Choi M, Vaga S, Vitek O, Saez-Rodriguez J, Aebersold R.

2016

doi:10.1101/051508.

Genome-wide chemical mutagenesis screens allow unbiased saturation of the cancer genome and identification of drug resistance mutations

Brammeld JS, Petljak M, Martincorena I, Williams SP, Garcia Alonso L, Dalmases A, Bellosillo B, Robles-Espinoza CD, Price S, Barthorpe S, Tarpey P, Alifrangis C, Bignell G, Vidal J, Young J, Stebbings L, Beal K, Stratton MR, Saez-Rodriguez J, Garnett M, Montagut C, Iorio F, McDermott U.

2016

doi:10.1101/066555.

Genomic determinants of protein abundance variation in colorectal cancer cells

Roumeliotis TI, Williams SP, Gonçalves E, Zamanzad Ghavidel F, Aben N, Michaut M, Schubert M, Wright JC, Yang M, Alsinet C, Dienstmann R, Guinney J, Beltrao P, Brazma A, Stegle O, Adams DJ, Wessels L, Saez-Rodriguez J, McDermott U, Choudhary JS.

2016

doi:10.1101/092767.

Dissecting cancer resistance to therapies with cell-type-specific dynamic logic models

Eduati F, Doldàn-Martelli V, Klinger B, Cokelaer T, Sieber A, Kogera F, Dorel M, Garnett MJ, Blüthgen N, Saez-Rodriguez J.

2016

doi:10.1101/094755.

Phosphoproteomics-based Profiling of Kinase Activities in Cancer Cells

Wirbel J, Rodriguez Cutillas P, Saez-Rodriguez J.

2016

doi:10.1101/066019.

Rapid identification of optimal drug combinations for personalized cancer therapy using microfluidics

Eduati F, Utharala R, Madhavan D, Neumann UP, Cramer T, Saez-Rodriguez J, Merten CA.

2016

doi:10.1101/093906.

Benchmarking substrate-based kinase activity inference using phosphoproteomic data

Hernandez-Armenta C, Ochoa D, Gonçalves E, Saez-Rodriguez J, Beltrao P.

2016

doi:10.1101/080978.

Chromosomal rearrangements are commonly post-transcriptionally attenuated in cancer

Gonçalves E, Fragoulis A, Garcia-Alonso L, Cramer T, Saez-Rodriguez J, Beltrao P.

2016

doi:10.1101/093369.

Efficient randomization of biological networks while preserving functional characterization of individual nodes.

Iorio F, Bernardo-Faura M, Gobbi A, Cokelaer T, Jurman G, Saez-Rodriguez J.

BMC Bioinformatics, 2016

doi:10.1186/s12859-016-1402-1.

OmniPath: guidelines and gateway for literature-curated signaling pathway resources.

Türei D, Korcsmáros T, Saez-Rodriguez J.

Nat Methods, 2016

doi:10.1038/nmeth.4077.

Looking beyond the cancer cell for effective drug combinations.

Dry JR, Yang M, Saez-Rodriguez J.

Genome Med, 2016

doi:10.1186/s13073-016-0379-8.

A CRISPR Dropout Screen Identifies Genetic Vulnerabilities and Therapeutic Targets in Acute Myeloid Leukemia.

Tzelepis K, Koike-Yusa H, De Braekeleer E, Li Y, Metzakopian E, Dovey OM, Mupo A, Grinkevich V, Li M, Mazan M, Gozdecka M, Ohnishi S, Cooper J, Patel M, McKerrell T, Chen B, Domingues AF, Gallipoli P, Teichmann S, Ponstingl H, McDermott U, Saez-Rodriguez J, Huntly BJP, Iorio F, Pina C, Vassiliou GS, Yusa K.

Cell Rep, 2016

doi:10.1016/j.celrep.2016.09.079.

Fumarate is an epigenetic modifier that elicits epithelial-to-mesenchymal transition.

Sciacovelli M, Gonçalves E, Johnson TI, Zecchini VR, da Costa AS, Gaude E, Drubbel AV, Theobald SJ, Abbo SR, Tran MG, Rajeeve V, Cardaci S, Foster S, Yun H, Cutillas P, Warren A, Gnanapragasam V, Gottlieb E, Franze K, Huntly B, Maher ER, Maxwell PH, Saez-Rodriguez J, Frezza C.

Nature, 2016

doi:10.1038/nature19353.

Crowdsourcing biomedical research: leveraging communities as innovation engines.

Saez-Rodriguez J, Costello JC, Friend SH, Kellen MR, Mangravite L, Meyer P, Norman T, Stolovitzky G.

Nat Rev Genet, 2016

doi:10.1038/nrg.2016.69.

A Landscape of Pharmacogenomic Interactions in Cancer.

Iorio F, Knijnenburg TA, Vis DJ, Bignell GR, Menden MP, Schubert M, Aben N, Gonçalves E, Barthorpe S, Lightfoot H, Cokelaer T, Greninger P, van Dyk E, Chang H, de Silva H, Heyn H, Deng X, Egan RK, Liu Q, Mironenko T, Mitropoulos X, Richardson L, Wang J, Zhang T, Moran S, Sayols S, Soleimani M, Tamborero D, Lopez-Bigas N, Ross-Macdonald P, Esteller M, Gray NS, Haber DA, Stratton MR, Benes CH, Wessels LFA, Saez-Rodriguez J, McDermott U, Garnett MJ.

Cell, 2016

doi:10.1016/j.cell.2016.06.017.

Logical Modeling and Dynamical Analysis of Cellular Networks.

Abou-Jaoudé W, Traynard P, Monteiro PT, Saez-Rodriguez J, Helikar T, Thieffry D, Chaouiya C.

Front Genet, 2016

doi:10.3389/fgene.2016.00094.

A computational method for designing diverse linear epitopes including citrullinated peptides with desired binding affinities to intravenous immunoglobulin.

Patro R, Norel R, Prill RJ, Saez-Rodriguez J, Lorenz P, Steinbeck F, Ziems B, Luštrek M, Barbarini N, Tiengo A, Bellazzi R, Thiesen HJ, Stolovitzky G, Kingsford C.

BMC Bioinformatics, 2016

doi:10.1186/s12859-016-1008-7.

Transcriptional response networks for elucidating mechanisms of action of multitargeted agents.

Kibble M, Khan SA, Saarinen N, Iorio F, Saez-Rodriguez J, Mäkelä S, Aittokallio T.

Drug Discov Today, 2016

doi:10.1016/j.drudis.2016.03.001.

Inferring causal molecular networks: empirical assessment through a community-based effort.

Hill SM, Heiser LM, Cokelaer T, Unger M, Nesser NK, Carlin DE, Zhang Y, Sokolov A, Paull EO, Wong CK, Graim K, Bivol A, Wang H, Zhu F, Afsari B, Danilova LV, Favorov AV, Lee WS, Taylor D, Hu CW, Long BL, Noren DP, Bisberg AJ, HPN-DREAM Consortium, Mills GB, Gray JW, Kellen M, Norman T, Friend S, Qutub AA, Fertig EJ, Guan Y, Song M, Stuart JM, Spellman PT, Koeppl H, Stolovitzky G, Saez-Rodriguez J, Mukherjee S.

Nat Methods, 2016

doi:10.1038/nmeth.3773.

Integrated transcriptomic and proteomic analysis identifies protein kinase CK2 as a key signaling node in an inflammatory cytokine network in ovarian cancer cells.

Kulbe H, Iorio F, Chakravarty P, Milagre CS, Moore R, Thompson RG, Everitt G, Canosa M, Montoya A, Drygin D, Braicu I, Sehouli J, Saez-Rodriguez J, Cutillas PR, Balkwill FR.

Oncotarget, 2016

doi:10.18632/oncotarget.7255.

Annexin A1 sustains tumor metabolism and cellular proliferation upon stable loss of HIF1A.

Rohwer N, Bindel F, Grimm C, Lin SJ, Wappler J, Klinger B, Blüthgen N, Du Bois I, Schmeck B, Lehrach H, de Graauw M, Goncalves E, Saez-Rodriguez J, Tan P, Grabsch HI, Prigione A, Kempa S, Cramer T.

Oncotarget, 2016

doi:10.18632/oncotarget.6793.

The orchestra of lipid-transfer proteins at the crossroads between metabolism and signaling.

Chiapparino A, Maeda K, Turei D, Saez-Rodriguez J, Gavin AC.

Prog Lipid Res, 2016

doi:10.1016/j.plipres.2015.10.004.

DREAMTools: a Python package for scoring collaborative challenges.

Cokelaer T, Bansal M, Bare C, Bilal E, Bot BM, Chaibub Neto E, Eduati F, de la Fuente A, Gönen M, Hill SM, Hoff B, Karr JR, Küffner R, Menden MP, Meyer P, Norel R, Pratap A, Prill RJ, Weirauch MT, Costello JC, Stolovitzky G, Saez-Rodriguez J.

F1000Res, 2015

doi:10.12688/f1000research.7118.2.

Pharmacogenomic agreement between two cancer cell line data sets.

Cancer Cell Line Encyclopedia Consortium, Genomics of Drug Sensitivity in Cancer Consortium.

Nature, 2015

doi:10.1038/nature15736.

Extended notions of sign consistency to relate experimental data to signaling and regulatory network topologies.

Thiele S, Cerone L, Saez-Rodriguez J, Siegel A, Guziołowski C, Klamt S.

BMC Bioinformatics, 2015

doi:10.1186/s12859-015-0733-7.

A Semi-Supervised Approach for Refining Transcriptional Signatures of Drug Response and Repositioning Predictions.

Iorio F, Shrestha RL, Levin N, Boilot V, Garnett MJ, Saez-Rodriguez J, Draviam VM.

PLoS One, 2015

doi:10.1371/journal.pone.0139446.

Designing Experiments to Discriminate Families of Logic Models.

Videla S, Konokotina I, Alexopoulos LG, Saez-Rodriguez J, Schaub T, Siegel A, Guziolowski C.

Front Bioeng Biotechnol, 2015

doi:10.3389/fbioe.2015.00131.

Large-scale models of signal propagation in human cells derived from discovery phosphoproteomic data.

Terfve CD, Wilkes EH, Casado P, Cutillas PR, Saez-Rodriguez J.

Nat Commun, 2015

doi:10.1038/ncomms9033.

Modeling Signaling Networks to Advance New Cancer Therapies.

Saez-Rodriguez J, MacNamara A, Cook S.

Annu Rev Biomed Eng, 2015

doi:10.1146/annurev-bioeng-071813-104927.

Prediction of human population responses to toxic compounds by a collaborative competition.

Eduati F, Mangravite LM, Wang T, Tang H, Bare JC, Huang R, Norman T, Kellen M, Menden MP, Yang J, Zhan X, Zhong R, Xiao G, Xia M, Abdo N, Kosyk O, NIEHS-NCATS-UNC DREAM Toxicogenetics Collaboration, Friend S, Dearry A, Simeonov A, Tice RR, Rusyn I, Wright FA, Stolovitzky G, Xie Y, Saez-Rodriguez J.

Nat Biotechnol, 2015

doi:10.1038/nbt.3299.

Integrative approaches for signalling and metabolic networks.

Hatzimanikatis V, Saez-Rodriguez J.

Integr Biol (Camb), 2015

doi:10.1039/c5ib90030a.

Empirical inference of circuitry and plasticity in a kinase signaling network.

Wilkes EH, Terfve C, Gribben JG, Saez-Rodriguez J, Cutillas PR.

Proc Natl Acad Sci U S A, 2015

doi:10.1073/pnas.1423344112.

A single-cell model of PIP3 dynamics using chemical dimerization.

MacNamara A, Stein F, Feng S, Schultz C, Saez-Rodriguez J.

Bioorg Med Chem, 2015

doi:10.1016/j.bmc.2015.04.074.

Reverse engineering of logic-based differential equation models using a mixed-integer dynamic optimization approach.

Henriques D, Rocha M, Saez-Rodriguez J, Banga JR.

Bioinformatics, 2015

doi:10.1093/bioinformatics/btv314.

Prospective derivation of a living organoid biobank of colorectal cancer patients.

van de Wetering M, Francies HE, Francis JM, Bounova G, Iorio F, Pronk A, van Houdt W, van Gorp J, Taylor-Weiner A, Kester L, McLaren-Douglas A, Blokker J, Jaksani S, Bartfeld S, Volckman R, van Sluis P, Li VS, Seepo S, Sekhar Pedamallu C, Cibulskis K, Carter SL, McKenna A, Lawrence MS, Lichtenstein L, Stewart C, Koster J, Versteeg R, van Oudenaarden A, Saez-Rodriguez J, Vries RG, Getz G, Wessels L, Stratton MR, McDermott U, Meyerson M, Garnett MJ, Clevers H.

Cell, 2015

doi:10.1016/j.cell.2015.03.053.

Identification of drug-specific pathways based on gene expression data: application to drug induced lung injury.

Melas IN, Sakellaropoulos T, Iorio F, Alexopoulos LG, Loh WY, Lauffenburger DA, Saez-Rodriguez J, Bai JP.

Integr Biol (Camb), 2015

doi:10.1039/c4ib00294f.

BioPreDyn-bench: a suite of benchmark problems for dynamic modelling in systems biology.

Villaverde AF, Henriques D, Smallbone K, Bongard S, Schmid J, Cicin-Sain D, Crombach A, Saez-Rodriguez J, Mauch K, Balsa-Canto E, Mendes P, Jaeger J, Banga JR.

BMC Syst Biol, 2015

doi:10.1186/s12918-015-0144-4.

Cooperative development of logical modelling standards and tools with CoLoMoTo.

Naldi A, Monteiro PT, Müssel C, Consortium for Logical Models and Tools, Kestler HA, Thieffry D, Xenarios I, Saez-Rodriguez J, Helikar T, Chaouiya C.

Bioinformatics, 2015

doi:10.1093/bioinformatics/btv013.

Signaling networks in MS: a systems-based approach to developing new pharmacological therapies.

Kotelnikova E, Bernardo-Faura M, Silberberg G, Kiani NA, Messinis D, Melas IN, Artigas L, Schwartz E, Mazo I, Masso M, Alexopoulos LG, Mas JM, Olsson T, Tegner J, Martin R, Zamora A, Paul F, Saez-Rodriguez J, Villoslada P.

Mult Scler, 2015

doi:10.1177/1352458514543339.

Cooperative development of logical modelling standards and tools with CoLoMoTo

Naldi A, Monteiro PT, Müssel C, Kestler HA, Thieffry D, Xenarios I, Saez-Rodriguez J, Helikar T, Chaouiya C, the Consortium for Logical Models and Tools.

2014

doi:10.1101/010504.

Phosphoproteomic analyses reveal novel cross-modulation mechanisms between two signaling pathways in yeast.

Vaga S, Bernardo-Faura M, Cokelaer T, Maiolica A, Barnes CA, Gillet LC, Hegemann B, van Drogen F, Sharifian H, Klipp E, Peter M, Saez-Rodriguez J, Aebersold R.

Mol Syst Biol, 2014

doi:10.15252/msb.20145112.

A community computational challenge to predict the activity of pairs of compounds.

Bansal M, Yang J, Karan C, Menden MP, Costello JC, Tang H, Xiao G, Li Y, Allen J, Zhong R, Chen B, Kim M, Wang T, Heiser LM, Realubit R, Mattioli M, Alvarez MJ, Shen Y, NCI-DREAM Community, Gallahan D, Singer D, Saez-Rodriguez J, Xie Y, Stolovitzky G, Califano A, NCI-DREAM Community.

Nat Biotechnol, 2014

doi:10.1038/nbt.3052.

Dynamic transcription factor activity and networks during ErbB2 breast oncogenesis and targeted therapy.

Weiss MS, Peñalver Bernabé B, Shin S, Asztalos S, Dubbury SJ, Mui MD, Bellis AD, Bluver D, Tonetti DA, Saez-Rodriguez J, Broadbelt LJ, Jeruss JS, Shea LD.

Integr Biol (Camb), 2014

doi:10.1039/c4ib00086b.

Fast randomization of large genomic datasets while preserving alteration counts.

Gobbi A, Iorio F, Dawson KJ, Wedge DC, Tamborero D, Alexandrov LB, Lopez-Bigas N, Garnett MJ, Jurman G, Saez-Rodriguez J.

Bioinformatics, 2014

doi:10.1093/bioinformatics/btu474.

Exhaustively characterizing feasible logic models of a signaling network using Answer Set Programming

Bioinformatics, 2014

doi:10.1093/bioinformatics/btu357.

A model integration approach linking signalling and gene-regulatory logic with kinetic metabolic models.

Ryll A, Bucher J, Bonin A, Bongard S, Gonçalves E, Saez-Rodriguez J, Niklas J, Klamt S.

Biosystems, 2014

doi:10.1016/j.biosystems.2014.07.002.

MEIGO: an open-source software suite based on metaheuristics for global optimization in systems biology and bioinformatics.

Egea JA, Henriques D, Cokelaer T, Villaverde AF, MacNamara A, Danciu DP, Banga JR, Saez-Rodriguez J.

BMC Bioinformatics, 2014

doi:10.1186/1471-2105-15-136.

A community effort to assess and improve drug sensitivity prediction algorithms.

Costello JC, Heiser LM, Georgii E, Gönen M, Menden MP, Wang NJ, Bansal M, Ammad-ud-din M, Hintsanen P, Khan SA, Mpindi JP, Kallioniemi O, Honkela A, Aittokallio T, Wennerberg K, NCI DREAM Community, Collins JJ, Gallahan D, Singer D, Saez-Rodriguez J, Kaski S, Gray JW, Stolovitzky G.

Nat Biotechnol, 2014

doi:10.1038/nbt.2877.

A rapidly reversible chemical dimerizer system to study lipid signaling in living cells.

Feng S, Laketa V, Stein F, Rutkowska A, MacNamara A, Depner S, Klingmüller U, Saez-Rodriguez J, Schultz C.

Angew Chem Int Ed Engl, 2014

doi:10.1002/anie.201402294.

Network topology and parameter estimation: from experimental design methods to gene regulatory network kinetics using a community based approach.

Meyer P, Cokelaer T, Chandran D, Kim KH, Loh PR, Tucker G, Lipson M, Berger B, Kreutz C, Raue A, Steiert B, Timmer J, Bilal E, Sauro HM, Stolovitzky G, Saez-Rodriguez J.

BMC Syst Biol, 2014

doi:10.1186/1752-0509-8-13.

PIP₃ induces the recycling of receptor tyrosine kinases.

Laketa V, Zarbakhsh S, Traynor-Kaplan A, Macnamara A, Subramanian D, Putyrski M, Mueller R, Nadler A, Mentel M, Saez-Rodriguez J, Pepperkok R, Schultz C.

Sci Signal, 2014

doi:10.1126/scisignal.2004532.

Cyrface: An interface from Cytoscape to R that provides a user interface to R packages.

Gonçalves E, Mirlach F, Saez-Rodriguez J.

F1000Res, 2013

doi:10.12688/f1000research.2-192.v2.

Network based elucidation of drug response: from modulators to targets.

Iorio F, Saez-Rodriguez J, di Bernardo D.

BMC Syst Biol, 2013

doi:10.1186/1752-0509-7-139.

SBML qualitative models: a model representation format and infrastructure to foster interactions between qualitative modelling formalisms and tools.

Chaouiya C, Bérenguier D, Keating SM, Naldi A, van Iersel MP, Rodriguez N, Dräger A, Büchel F, Cokelaer T, Kowal B, Wicks B, Gonçalves E, Dorier J, Page M, Monteiro PT, von Kamp A, Xenarios I, de Jong H, Hucka M, Klamt S, Thieffry D, Le Novère N, Saez-Rodriguez J, Helikar T.

BMC Syst Biol, 2013

doi:10.1186/1752-0509-7-135.

Path2Models: large-scale generation of computational models from biochemical pathway maps.

Büchel F, Rodriguez N, Swainston N, Wrzodek C, Wrzodek C, Czauderna T, Keller R, Mittag F, Schubert M, Glont M, Golebiewski M, van Iersel M, Keating S, Rall M, Wybrow M, Hermjakob H, Hucka M, Kell DB, Müller W, Mendes P, Zell A, Chaouiya C, Saez-Rodriguez J, Schreiber F, Laibe C, Dräger A, Le Novère N.

BMC Syst Biol, 2013

doi:10.1186/1752-0509-7-116.

BioServices: a common Python package to access biological Web Services programmatically.

Cokelaer T, Pultz D, Harder LM, Serra-Musach J, Saez-Rodriguez J.

Bioinformatics, 2013

doi:10.1093/bioinformatics/btt547.

Exhaustively characterizing feasible logic models of a signaling network using Answer Set Programming.

Guziolowski C, Videla S, Eduati F, Thiele S, Cokelaer T, Siegel A, Saez-Rodriguez J.

Bioinformatics, 2013

doi:10.1093/bioinformatics/btt393.

Modeling signaling networks with different formalisms: a preview.

MacNamara A, Henriques D, Saez-Rodriguez J.

Methods Mol Biol, 2013

doi:10.1007/978-1-62703-450-0_5.

Machine learning prediction of cancer cell sensitivity to drugs based on genomic and chemical properties.

Menden MP, Iorio F, Garnett M, McDermott U, Benes CH, Ballester PJ, Saez-Rodriguez J.

PLoS One, 2013

doi:10.1371/journal.pone.0061318.

Phosphoproteomics data classify hematological cancer cell lines according to tumor type and sensitivity to kinase inhibitors.

Casado P, Alcolea MP, Iorio F, Rodríguez-Prados JC, Rodríguez-Prados JC, Vanhaesebroeck B, Saez-Rodriguez J, Joel S, Cutillas PR.

Genome Biol, 2013

doi:10.1186/gb-2013-14-4-r37.

Bridging the layers: towards integration of signal transduction, regulation and metabolism into mathematical models.

Gonçalves E, Bucher J, Ryll A, Niklas J, Mauch K, Klamt S, Rocha M, Saez-Rodriguez J.

Mol Biosyst, 2013

doi:10.1039/c3mb25489e.

Critical assessment of automated flow cytometry data analysis techniques.

Aghaeepour N, Finak G, FlowCAP Consortium, DREAM Consortium, Hoos H, Mosmann TR, Brinkman R, Gottardo R, Scheuermann RH.

Nat Methods, 2013

doi:10.1038/nmeth.2365.

Evaluation of methods for modeling transcription factor sequence specificity.

Weirauch MT, Cote A, Norel R, Annala M, Zhao Y, Riley TR, Saez-Rodriguez J, Cokelaer T, Vedenko A, Talukder S, DREAM5 Consortium, Bussemaker HJ, Morris QD, Bulyk ML, Stolovitzky G, Hughes TR.

Nat Biotechnol, 2013

doi:10.1038/nbt.2486.

CySBGN: a Cytoscape plug-in to integrate SBGN maps.

Gonçalves E, van Iersel M, Saez-Rodriguez J.

BMC Bioinformatics, 2013

doi:10.1186/1471-2105-14-17.

DvD: An R/Cytoscape pipeline for drug repurposing using public repositories of gene expression data.

Pacini C, Iorio F, Gonçalves E, Iskar M, Iskar M, Klabunde T, Bork P, Saez-Rodriguez J.

Bioinformatics, 2013

doi:10.1093/bioinformatics/bts656.

Construction of cell type-specific logic models of signaling networks using CellNOpt.

Morris MK, Melas I, Saez-Rodriguez J.

Methods Mol Biol, 2013

doi:10.1007/978-1-62703-059-5_8.

Transcriptional data: a new gateway to drug repositioning?

Iorio F, Rittman T, Ge H, Menden M, Saez-Rodriguez J.

Drug Discov Today, 2013

doi:10.1016/j.drudis.2012.07.014.

Revisiting the training of logic models of protein signaling networks with ASP

Videla S, Guziolowski C, Eduati F, Thiele S, Grabe N, Saez-Rodriguez J, Siegel A.

2012

doi:10.1007/978-3-642-33636-2_20.

Non Linear Programming (NLP) formulation for quantitative modeling of protein signal transduction pathways.

Mitsos A, Melas IN, Morris MK, Saez-Rodriguez J, Lauffenburger DA, Alexopoulos LG.

PLoS One, 2012

doi:10.1371/journal.pone.0050085.

CellNOptR: a flexible toolkit to train protein signaling networks to data using multiple logic formalisms.

Terfve C, Cokelaer T, Henriques D, MacNamara A, Goncalves E, Morris MK, van Iersel M, Lauffenburger DA, Saez-Rodriguez J.

BMC Syst Biol, 2012

doi:10.1186/1752-0509-6-133.

Mapping the human phosphatome on growth pathways.

Sacco F, Gherardini PF, Paoluzi S, Saez-Rodriguez J, Helmer-Citterich M, Ragnini-Wilson A, Castagnoli L, Cesareni G.

Mol Syst Biol, 2012

doi:10.1038/msb.2012.36.

State-time spectrum of signal transduction logic models.

MacNamara A, Terfve C, Henriques D, Bernabé BP, Saez-Rodriguez J.

Phys Biol, 2012

doi:10.1088/1478-3975/9/4/045003.

Cancer develops, progresses and responds to therapies through restricted perturbation of the protein-protein interaction network.

Serra-Musach J, Aguilar H, Iorio F, Comellas F, Berenguer A, Brunet J, Saez-Rodriguez J, Pujana MA.

Integr Biol (Camb), 2012

doi:10.1039/c2ib20052j.

Integrating literature-constrained and data-driven inference of signalling networks.

Eduati F, De Las Rivas J, Di Camillo B, Toffolo G, Saez-Rodriguez J.

Bioinformatics, 2012

doi:10.1093/bioinformatics/bts363.

Creating and analyzing pathway and protein interaction compendia for modelling signal transduction networks.

Kirouac DC, Saez-Rodriguez J, Swantek J, Burke JM, Lauffenburger DA, Sorger PK.

BMC Syst Biol, 2012

doi:10.1186/1752-0509-6-29.

Systematic identification of genomic markers of drug sensitivity in cancer cells.

Garnett MJ, Edelman EJ, Heidorn SJ, Greenman CD, Dastur A, Lau KW, Greninger P, Thompson IR, Luo X, Soares J, Liu Q, Iorio F, Surdez D, Chen L, Milano RJ, Bignell GR, Tam AT, Davies H, Stevenson JA, Barthorpe S, Lutz SR, Kogera F, Lawrence K, McLaren-Douglas A, Mitropoulos X, Mironenko T, Thi H, Richardson L, Zhou W, Jewitt F, Zhang T, O'Brien P, Boisvert JL, Price S, Hur W, Yang W, Deng X, Butler A, Choi HG, Chang JW, Baselga J, Stamenkovic I, Engelman JA, Sharma SV, Delattre O, Saez-Rodriguez J, Gray NS, Settleman J, Futreal PA, Haber DA, Stratton MR, Ramaswamy S, McDermott U, Benes CH.

Nature, 2012

doi:10.1038/nature11005.

Construction of large signaling pathways using an adaptive perturbation approach with phosphoproteomic data.

Melas IN, Mitsos A, Messinis DE, Weiss TS, Rodriguez JS, Alexopoulos LG.

Mol Biosyst, 2012

doi:10.1039/c2mb05482e.

Modeling signaling networks using high-throughput phospho-proteomics.

Terfve C, Saez-Rodriguez J.

Adv Exp Med Biol, 2012

doi:10.1007/978-1-4419-7210-1_2.

Retroactivity as a Criterion to Define Modules in Signaling Networks

Saez-Rodriguez J, Conzelmann H, Ederer M, Gilles ED.

2011

doi:10.1007/978-1-4419-6766-4_7.

Crowdsourcing network inference: the DREAM predictive signaling network challenge.

Prill RJ, Saez-Rodriguez J, Alexopoulos LG, Sorger PK, Stolovitzky G.

Sci Signal, 2011

doi:10.1126/scisignal.2002212.

Comparing signaling networks between normal and transformed hepatocytes using discrete logical models.

Saez-Rodriguez J, Alexopoulos LG, Zhang M, Morris MK, Lauffenburger DA, Sorger PK.

Cancer Res, 2011

doi:10.1158/0008-5472.can-10-4453.

Training signaling pathway maps to biochemical data with constrained fuzzy logic: quantitative analysis of liver cell responses to inflammatory stimuli.

Morris MK, Saez-Rodriguez J, Clarke DC, Sorger PK, Lauffenburger DA.

PLoS Comput Biol, 2011

doi:10.1371/journal.pcbi.1001099.

Setting the standards for signal transduction research.

Saez-Rodriguez J, Alexopoulos LG, Stolovitzky G.

Sci Signal, 2011

doi:10.1126/scisignal.2001844.

Construction of signaling pathways and identification of drug effects on the liver cancer cell HepG2.

Alexopoulos LG, Melas IN, Chairakaki AD, Saez-Rodriguez J, Mitsos A.

Annu Int Conf IEEE Eng Med Biol Soc, 2010

doi:10.1109/iembs.2010.5626246.

Networks inferred from biochemical data reveal profound differences in toll-like receptor and inflammatory signaling between normal and transformed hepatocytes.

Alexopoulos LG, Saez-Rodriguez J, Cosgrove BD, Lauffenburger DA, Sorger PK.

Mol Cell Proteomics, 2010

doi:10.1074/mcp.m110.000406.

Correction: Towards a Rigorous Assessment of Systems Biology Models: The DREAM3 Challenges

PLoS One, 2010

doi:.

Logic-based models for the analysis of cell signaling networks.

Morris MK, Saez-Rodriguez J, Sorger PK, Lauffenburger DA.

Biochemistry, 2010

doi:10.1021/bi902202q.

Towards a rigorous assessment of systems biology models: the DREAM3 challenges.

Prill RJ, Marbach D, Saez-Rodriguez J, Sorger PK, Alexopoulos LG, Xue X, Clarke ND, Altan-Bonnet G, Stolovitzky G.

PLoS One, 2010

doi:10.1371/journal.pone.0009202.

Cellular Regulatory Networks

Joughin BA, Cheung E, Karuturi RKM, Saez-Rodriguez J, Lauffenburger DA, Liu ET.

2009

doi:10.1016/b978-0-12-372550-9.00004-3.

Identifying drug effects via pathway alterations using an integer linear programming optimization formulation on phosphoproteomic data.

Mitsos A, Melas IN, Siminelakis P, Chairakaki AD, Saez-Rodriguez J, Alexopoulos LG.

PLoS Comput Biol, 2009

doi:10.1371/journal.pcbi.1000591.

A multipathway phosphoproteomic signaling network model of idiosyncratic drug- and inflammatory cytokine-induced toxicity in human hepatocytes.

Cosgrove BD, Alexopoulos LG, Saez-Rodriguez J, Griffith LG, Lauffenburger DA.

Annu Int Conf IEEE Eng Med Biol Soc, 2009

doi:10.1109/iembs.2009.5334019.

Discrete logic modelling as a means to link protein signalling networks with functional analysis of mammalian signal transduction.

Saez-Rodriguez J, Alexopoulos LG, Epperlein J, Samaga R, Lauffenburger DA, Klamt S, Sorger PK.

Mol Syst Biol, 2009

doi:10.1038/msb.2009.87.

Transforming Boolean models to continuous models: methodology and application to T-cell receptor signaling.

Wittmann DM, Krumsiek J, Saez-Rodriguez J, Lauffenburger DA, Klamt S, Theis FJ.

BMC Syst Biol, 2009

doi:10.1186/1752-0509-3-98.

The logic of EGFR/ErbB signaling: theoretical properties and analysis of high-throughput data.

Samaga R, Saez-Rodriguez J, Alexopoulos LG, Sorger PK, Klamt S.

PLoS Comput Biol, 2009

doi:10.1371/journal.pcbi.1000438.

Fuzzy logic analysis of kinase pathway crosstalk in TNF/EGF/insulin-induced signaling.

Aldridge BB, Saez-Rodriguez J, Muhlich JL, Sorger PK, Lauffenburger DA.

PLoS Comput Biol, 2009

doi:10.1371/journal.pcbi.1000340.

High-throughput protein-based technologies and computational models for drug development, efficacy, and toxicity

Alexopoulos LG, Saez-Rodriguez J, Espelin CW.

2008

doi:10.1002/9780470431818.ch2.

Automatic decomposition of kinetic models of signaling networks minimizing the retroactivity among modules.

Saez-Rodriguez J, Gayer S, Ginkel M, Gilles ED.

Bioinformatics, 2008

doi:10.1093/bioinformatics/btn289.

Dynamics of proximal signaling events after TCR/CD8-mediated induction of proliferation or apoptosis in mature CD8+ T cells.

Wang X, Simeoni L, Lindquist JA, Saez-Rodriguez J, Ambach A, Gilles ED, Kliche S, Schraven B.

J Immunol, 2008

doi:10.4049/jimmunol.180.10.6703.

Multistability of signal transduction motifs.

Saez-Rodriguez J, Hammerle-Fickinger A, Dalal O, Klamt S, Gilles ED, Conradi C.

IET Syst Biol, 2008

doi:10.1049/iet-syb:20070012.

Flexible informatics for linking experimental data to mathematical models via DataRail.

Saez-Rodriguez J, Goldsipe A, Muhlich J, Alexopoulos LG, Millard B, Lauffenburger DA, Sorger PK.

Bioinformatics, 2008

doi:10.1093/bioinformatics/btn018.

A logical model provides insights into T cell receptor signaling.

Saez-Rodriguez J, Simeoni L, Lindquist JA, Hemenway R, Bommhardt U, Arndt B, Haus UU, Weismantel R, Gilles ED, Klamt S, Schraven B.

PLoS Comput Biol, 2007

doi:10.1371/journal.pcbi.0030163.

Structural and functional analysis of cellular networks with CellNetAnalyzer.

Klamt S, Saez-Rodriguez J, Gilles ED.

BMC Syst Biol, 2007

doi:10.1186/1752-0509-1-2.

Systems biology--an engineering perspective.

Kremling A, Saez-Rodriguez J.

J Biotechnol, 2007

doi:10.1016/j.jbiotec.2007.02.009.

Chemical Reaction Network Theory: a tool for systems biology

Conradi C, Saez-Rodriguez J, Gilles ED, Raisch J.

2006

doi:.

Visual setup of logical models of signaling and regulatory networks with ProMoT.

Saez-Rodriguez J, Mirschel S, Hemenway R, Klamt S, Gilles ED, Ginkel M.

BMC Bioinformatics, 2006

doi:10.1186/1471-2105-7-506.

A methodology for the structural and functional analysis of signaling and regulatory networks.

Klamt S, Saez-Rodriguez J, Lindquist JA, Simeoni L, Gilles ED.

BMC Bioinformatics, 2006

doi:10.1186/1471-2105-7-56.

A domain-oriented approach to the reduction of combinatorial complexity in signal transduction networks.

Conzelmann H, Saez-Rodriguez J, Sauter T, Kholodenko BN, Gilles ED.

BMC Bioinformatics, 2006

doi:10.1186/1471-2105-7-34.

Dissecting the puzzle of life: modularization of signal transduction networks

Saez-Rodriguez J, Kremling A, Gilles ED.

Comput Chem Eng, 2005

doi:10.1016/j.compchemeng.2004.08.035.

Domain-oriented and modular approaches to the reduction of mathematical models of signaling networks

Saez-Rodriguez J, Conzelmann H, Sauter T, Kholodenko BN, Gilles ED.

2005

doi:.

Using chemical reaction network theory to discard a kinetic mechanism hypothesis.

Conradi C, Saez-Rodriguez J, Gilles ED, Raisch J.

Syst Biol (Stevenage), 2005

doi:10.1049/ip-syb:20050045.

Modular analysis of signal transduction networks

Saez-Rodriguez J, Kremling A, Conzelmann H, Bettenbrock K, Gilles ED.

IEEE Control Syst, 2004

doi:10.1109/mcs.2004.1316652.

Reduction of mathematical models of signal transduction networks: simulation-based approach applied to EGF receptor signalling.

Conzelmann H, Saez-Rodriguez J, Sauter T, Bullinger E, Allgöwer F, Gilles ED.

Syst Biol (Stevenage), 2004

doi:10.1049/sb:20045011.