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Mitsopoulos, Costas; Di Micco, Patrizio; Fernandez, Eloy Villasclaras; Dolciami, Daniela; Holt, Esty; Mica, Ioan L; Coker, Elizabeth A; Tym, Joseph E; Campbell, James; Che, Ka Hing; Ozer, Bugra; Kannas, Christos; Antolin, Albert A; Workman, Paul; Al-Lazikani, Bissan
Nucleic acids research, 01/2021, Letnik: 49, Številka: D1Journal Article
Abstract canSAR (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.
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Dostop do baze podatkov JCR je dovoljen samo uporabnikom iz Slovenije. Vaš trenutni IP-naslov ni na seznamu dovoljenih za dostop, zato je potrebna avtentikacija z ustreznim računom AAI.
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JCR | SNIP | JCR | SNIP | JCR | SNIP | JCR | SNIP |
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Povezave do osebnih bibliografij avtorjev | Povezave do podatkov o raziskovalcih v sistemu SICRIS |
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Vir: Osebne bibliografije
in: SICRIS
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