{"id":8484,"date":"2016-11-15T10:23:29","date_gmt":"2016-11-15T09:23:29","guid":{"rendered":"https:\/\/news.embl.de\/?p=8484"},"modified":"2024-03-25T10:07:38","modified_gmt":"2024-03-25T09:07:38","slug":"1611-new-bioinformatics-method-imaging-mass-spectrometry","status":"publish","type":"post","link":"https:\/\/www.embl.org\/news\/science\/1611-new-bioinformatics-method-imaging-mass-spectrometry\/","title":{"rendered":"Improving data analysis in imaging mass spec"},"content":{"rendered":"\n<p>Scientists in Theodore Alexandrov\u2019s lab at EMBL have developed the first bioinformatics framework for finding metabolites in large datasets from imaging mass spectrometry. The framework and open-source software, published today in <em>Nature Methods<\/em>, mimic how people manually analyse such data, but is unbiased, and a million times faster than a human. To create it, the EMBL scientists had to develop a way to estimate false discovery rate \u2013 the percentage of molecules identified in a mass spectrometry experiment that are not actually in the sample. This was a first not just for spatial metabolomics, but also for metabolomics in general. Having an estimate of false discovery rate incorporated in the system is crucial for anyone wanting to compare the results of experiments conducted in different labs, or across different species.<\/p>\n\n\n\n<p>The software is already being used by Alexandrov and collaborators in the EC-funded consortium METASPACE. The scientists are working with Christoph Steinbeck\u2019s team at EMBL-EBI so that the raw imaging data uploaded to the MetaboLights repository can be annotated with information about what molecules it contains. This would make it easier for biologists to extract the information that\u2019s relevant to them from such datasets. Alexandrov\u2019s team is also collaborating with several major pharma companies to integrate this new method into their drug discovery workflows.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Open source bioinformatics method for finding metabolites makes experiments comparable across labs<\/p>\n","protected":false},"author":8,"featured_media":8492,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[2,17591],"tags":[416,28,36,43,248,219,473],"embl_taxonomy":[],"class_list":["post-8484","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-science","category-science-technology","tag-alexandrov","tag-bioinformatics","tag-embl-ebi","tag-heidelberg","tag-mass-spectrometry","tag-metabolomics","tag-steinbeck"],"acf":{"article_intro":"<p>Open source bioinformatics method for finding metabolites makes experiments comparable across labs<\/p>\n","related_links":[{"link_description":"Alexandrov team","link_url":"http:\/\/www.embl.de\/research\/units\/scb\/alexandrov\/"},{"link_description":"METASPACE","link_url":"http:\/\/metaspace2020.eu\/"},{"link_description":"MetaboLights","link_url":"http:\/\/www.ebi.ac.uk\/metabolights\/"},{"link_description":"Steinbeck group","link_url":"http:\/\/www.ebi.ac.uk\/research\/steinbeck"}],"article_sources":[{"source_description":"<p>Palmer et al. Nature Methods, published online 14 November 2016. DOI: 10.1038\/nmeth.4072<\/p>\n","source_link_url":"http:\/\/www.nature.com\/nmeth\/journal\/vaop\/ncurrent\/full\/nmeth.4072.html"}],"vf_locked":false,"featured":false,"color":"#007B53"},"embl_taxonomy_terms":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.2 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>New bioinformatics method for imaging mass spectrometry by EMBL<\/title>\n<meta name=\"description\" content=\"Open source bioinformatics method for finding metabolites makes experiments comparable across labs. This method is developed by the Alexandrov team at EMBL.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.embl.org\/news\/science\/1611-new-bioinformatics-method-imaging-mass-spectrometry\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"New bioinformatics method for imaging mass spectrometry by EMBL\" \/>\n<meta property=\"og:description\" content=\"Open source bioinformatics method for finding metabolites makes experiments comparable across labs. This method is developed by the Alexandrov team at EMBL.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.embl.org\/news\/science\/1611-new-bioinformatics-method-imaging-mass-spectrometry\/\" \/>\n<meta property=\"og:site_name\" content=\"EMBL\" \/>\n<meta property=\"article:publisher\" content=\"https:\/\/www.facebook.com\/embl.org\/\" \/>\n<meta property=\"article:published_time\" content=\"2016-11-15T09:23:29+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2024-03-25T09:07:38+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/www.embl.org\/news\/wp-content\/uploads\/2016\/11\/1611_mass-spec-software_ib1-1.jpg\" \/>\n\t<meta property=\"og:image:width\" content=\"620\" \/>\n\t<meta property=\"og:image:height\" content=\"425\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/jpeg\" \/>\n<meta name=\"author\" content=\"Sonia Furtado Neves\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:creator\" content=\"@Aur_ora\" \/>\n<meta name=\"twitter:site\" content=\"@embl\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"Sonia Furtado Neves\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"1 minute\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"NewsArticle\",\"@id\":\"https:\/\/www.embl.org\/news\/science\/1611-new-bioinformatics-method-imaging-mass-spectrometry\/#article\",\"isPartOf\":{\"@id\":\"https:\/\/www.embl.org\/news\/science\/1611-new-bioinformatics-method-imaging-mass-spectrometry\/\"},\"author\":{\"name\":\"Sonia Furtado Neves\",\"@id\":\"https:\/\/www.embl.org\/news\/#\/schema\/person\/d926199a955624b44dda296f396c5e68\"},\"headline\":\"Improving data analysis in imaging mass spec\",\"datePublished\":\"2016-11-15T09:23:29+00:00\",\"dateModified\":\"2024-03-25T09:07:38+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\/\/www.embl.org\/news\/science\/1611-new-bioinformatics-method-imaging-mass-spectrometry\/\"},\"wordCount\":224,\"publisher\":{\"@id\":\"https:\/\/www.embl.org\/news\/#organization\"},\"image\":{\"@id\":\"https:\/\/www.embl.org\/news\/science\/1611-new-bioinformatics-method-imaging-mass-spectrometry\/#primaryimage\"},\"thumbnailUrl\":\"https:\/\/www.embl.org\/news\/wp-content\/uploads\/2016\/11\/1611_mass-spec-software_ib1-1.jpg\",\"keywords\":[\"alexandrov\",\"bioinformatics\",\"embl-ebi\",\"heidelberg\",\"mass spectrometry\",\"metabolomics\",\"steinbeck\"],\"articleSection\":[\"Science\",\"Science &amp; Technology\"],\"inLanguage\":\"en-US\"},{\"@type\":\"WebPage\",\"@id\":\"https:\/\/www.embl.org\/news\/science\/1611-new-bioinformatics-method-imaging-mass-spectrometry\/\",\"url\":\"https:\/\/www.embl.org\/news\/science\/1611-new-bioinformatics-method-imaging-mass-spectrometry\/\",\"name\":\"New bioinformatics method for imaging mass spectrometry by EMBL\",\"isPartOf\":{\"@id\":\"https:\/\/www.embl.org\/news\/#website\"},\"primaryImageOfPage\":{\"@id\":\"https:\/\/www.embl.org\/news\/science\/1611-new-bioinformatics-method-imaging-mass-spectrometry\/#primaryimage\"},\"image\":{\"@id\":\"https:\/\/www.embl.org\/news\/science\/1611-new-bioinformatics-method-imaging-mass-spectrometry\/#primaryimage\"},\"thumbnailUrl\":\"https:\/\/www.embl.org\/news\/wp-content\/uploads\/2016\/11\/1611_mass-spec-software_ib1-1.jpg\",\"datePublished\":\"2016-11-15T09:23:29+00:00\",\"dateModified\":\"2024-03-25T09:07:38+00:00\",\"description\":\"Open source bioinformatics method for finding metabolites makes experiments comparable across labs. 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