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Oxford University Press, Nucleic Acids Research, D1(51), p. D1212-D1219, 2022

DOI: 10.1093/nar/gkac1004

Oxford University Press, Nucleic Acids Research, D1(49), p. D1074-D1082, 2020

DOI: 10.1093/nar/gkaa1059

Oxford University Press, Nucleic Acids Research, D1(47), p. D917-D922, 2018

DOI: 10.1093/nar/gky1129

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canSAR: update to the cancer translational research and drug discovery knowledgebase

This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Data provided by SHERPA/RoMEO

Abstract

AbstractcanSAR (http://cansar.icr.ac.uk) is the largest, public, freely available, integrative translational research and drug discovery knowledgebase for oncology. canSAR integrates vast multidisciplinary data from across genomic, protein, pharmacological, drug and chemical data with structural biology, protein networks and more. It also provides unique data, curation and annotation and crucially, AI-informed target assessment for drug discovery. canSAR is widely used internationally by academia and industry. Here we describe significant developments and enhancements to the data, web interface and infrastructure of canSAR in the form of the new implementation of the system: canSARblack. We demonstrate new functionality in aiding translation hypothesis generation and experimental design, and show how canSAR can be adapted and utilised outside oncology.