Technological developments in microscopy have made cell biology a quantitative and data intensive discipline with many computational challenges.
Technological developments in microscopy have made cell biology a quantitative and data intensive discipline with many computational challenges. In particular, CBBCS activities involve:
CBBCS applies statistical and machine learning methods to extract biologically-relevant and interpretable insights from image-derived data and helps integrate omics-type data for effective interpretation of image-derived data.
With increasing requirements for making research data publicly available under the FAIR principles, CBBCS helps organise data for public release, assists with submitting data to suitable public repositories and setting up dedicated publicly accessible resources to support publications.
As projects increasingly cut across technologies and data types, CBBCS ensures that unit members have access to the relevant computational resources and expertise available in multiple EMBL support facilities and centres. In particular, CBBCS works with IT Services to implement compute resources that meet the needs of the unit.
CBBCS contributes to the development and teaching of various courses in computational biology provided by the EMBL Bio-IT community with the goal of making unit members better able to use available computational tools and implement their own computational solutions.