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dc.contributor.authorBiankin, AV
dc.contributor.authorGrimmond, SM
dc.date.accessioned2021-04-22T01:22:45Z
dc.date.available2021-04-22T01:22:45Z
dc.date.issued2013-02-28
dc.identifierpii: gm423
dc.identifier.citationBiankin, A. V. & Grimmond, S. M. (2013). Novel cancer drivers: mining the kinome. GENOME MEDICINE, 5 (2), https://doi.org/10.1186/gm423.
dc.identifier.issn1756-994X
dc.identifier.urihttp://hdl.handle.net/11343/269190
dc.description.abstractLarge-scale cancer genome studies are unveiling significant complexity and heterogeneity even in histopathologically indistinguishable cancers. Differentiating 'driver' mutations that are functionally relevant from 'passenger' mutations is a major challenge in cancer genomics. While recurrent mutations in a gene provides supporting evidence of 'driver' status, novel computational methods and model systems are greatly improving our ability to identify genes important in carcinogenesis. Reimand and Bader have recently shown that driver gene discovery in discrete gene classes (in this case the kinome) is possible across multiple cancer types and has the potential to yield new druggable targets and clinically relevant leads.
dc.languageEnglish
dc.publisherBMC
dc.titleNovel cancer drivers: mining the kinome
dc.typeJournal Article
dc.identifier.doi10.1186/gm423
melbourne.affiliation.departmentCentre for Cancer Research
melbourne.affiliation.facultyMedicine, Dentistry & Health Sciences
melbourne.source.titleGenome Medicine: medicine in the post-genomic era
melbourne.source.volume5
melbourne.source.issue2
melbourne.elementsid1033363
melbourne.openaccess.urlhttps://europepmc.org/articles/PMC3706765?pdf=render
melbourne.openaccess.statusPublished version
melbourne.contributor.authorGrimmond, Sean
dc.identifier.eissn1756-994X
melbourne.accessrightsAccess this item via the Open Access location


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