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dc.contributor.authorMitsopoulos, C
dc.contributor.authorDi Micco, P
dc.contributor.authorFernandez, EV
dc.contributor.authorDolciami, D
dc.contributor.authorHolt, E
dc.contributor.authorMica, IL
dc.contributor.authorCoker, EA
dc.contributor.authorTym, JE
dc.contributor.authorCampbell, J
dc.contributor.authorChe, KH
dc.contributor.authorOzer, B
dc.contributor.authorKannas, C
dc.contributor.authorAntolin, AA
dc.contributor.authorWorkman, P
dc.contributor.authorAl-Lazikani, B
dc.date.accessioned2020-12-01T17:09:40Z
dc.date.issued2021-01-08
dc.identifier.citationNucleic acids research, 2021, 49 (D1), pp. D1074 - D1082
dc.identifier.issn0305-1048
dc.identifier.urihttps://repository.icr.ac.uk/handle/internal/4251
dc.identifier.eissn1362-4962
dc.identifier.doi10.1093/nar/gkaa1059
dc.description.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.
dc.formatPrint
dc.format.extentD1074 - D1082
dc.languageeng
dc.language.isoeng
dc.publisherOXFORD UNIV PRESS
dc.rights.urihttps://creativecommons.org/licenses/by/4.0
dc.titlecanSAR: update to the cancer translational research and drug discovery knowledgebase.
dc.typeJournal Article
dcterms.dateAccepted2020-10-27
rioxxterms.versionofrecord10.1093/nar/gkaa1059
rioxxterms.licenseref.urihttps://creativecommons.org/licenses/by/4.0
rioxxterms.licenseref.startdate2021-01
rioxxterms.typeJournal Article/Review
dc.relation.isPartOfNucleic acids research
pubs.issueD1
pubs.notesNot known
pubs.organisational-group/ICR
pubs.organisational-group/ICR/Primary Group
pubs.organisational-group/ICR/Primary Group/ICR Divisions
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Cancer Therapeutics
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Cancer Therapeutics/Computational Biology and Chemogenomics
pubs.organisational-group/ICR
pubs.organisational-group/ICR/Primary Group
pubs.organisational-group/ICR/Primary Group/ICR Divisions
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Cancer Therapeutics
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Cancer Therapeutics/Computational Biology and Chemogenomics
pubs.publication-statusPublished
pubs.volume49
pubs.embargo.termsNot known
icr.researchteamComputational Biology and Chemogenomics
dc.contributor.icrauthorMitsopoulos, Konstantinos
dc.contributor.icrauthorCampbell, James
dc.contributor.icrauthorWorkman, Paul
dc.contributor.icrauthorAl-Lazikani, Bissan


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