canSAR Team in the Department of Data Science
Cancer Therapeutics Unit
The Institute of Cancer Research
canSAR is an integrated knowledge-base that brings together multidisciplinary data across biology, chemistry, pharmacology, structural biology, cellular networks and clinical annotations, and applies machine learning approaches to provide drug-discovery useful predictions.
canSAR’s goal is to enable cancer translational research and drug discovery through providing this knowledge to researchers from across different disciplines. It provides a single information portal to answer complex multi-disciplinary questions including - among many others: what is known about a protein, in which cancers is it expressed or mutated and what chemical tools and cell line models can be used to experimentally probe its activity? What is known about a drug, its cellular sensitivity profile and what proteins is it known to bind that may explain unusual bioactivity?
please contact the ICR media office on 0207 153 5380 if you have publicity or media related queries.
canSAR works on Firefox, Chrome and Safari. We do not support Internet Explorer as it is non-standards compliant.
To view statistics of canSAR data please refer to the Data Sources. Data Sources.
canSAR is funded by the Cancer Research UK Drug Discovery Committee strategic award ‘canSAR: enhancing the drug discovery knowledgebase’ C35696/A23187, previously C309/A11566, C309/A8274.
Thanks to all our collaborators and data providers especially the following:
The Beckwith family for donating a high performance computing system.
canSAR is developed by the canSAR Team in the Department of Data Science in association with the Cancer Therapeutics Unit. We thank other colleagues and team members, past and present, for their contributions, especially: Prof. Paul Workman, Parisa Razaz, Costas Mitsopoulos, Mishal Patel and Mark Halling-Brown.