Patient-specific driver gene prediction and risk assessment through integrated network analysis of cancer omics profiles

Extensive and multi-dimensional data sets generated from recent cancer omics profiling projects have presented new challenges and opportunities for unraveling the complexity of cancer genome landscapes. In particular, distinguishing the unique complement of genes that drive tumorigenesis in each pat...

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Detalles Bibliográficos
Autores principales: Bertrand, Denis, Chng, Kern Rei, Sherbaf, Faranak Ghazi, Kiesel, Anja, Chia, Burton K. H., Sia, Yee Yen, Huang, Sharon K., Hoon, Dave S.B., Liu, Edison T., Hillmer, Axel, Nagarajan, Niranjan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2015
Materias:
Methods Online
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4402507/
https://www.ncbi.nlm.nih.gov/pubmed/25572314
http://dx.doi.org/10.1093/nar/gku1393

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4402507/
https://www.ncbi.nlm.nih.gov/pubmed/25572314
http://dx.doi.org/10.1093/nar/gku1393

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