Adjusting for background mutation frequency biases improves the identification of cancer driver genes.

Evans, Perry; Avey, Stefan; Kong, Yong; Krauthammer, Michael

Evans, Perry; Avey, Stefan; Kong, Yong; Krauthammer, Michael.

Affiliation

Evans P; Department of Pathology, Yale University School of Medicine, New Haven, CT 06511, USA.

IEEE Trans Nanobioscience ; 12(3): 150-7, 2013 Sep.

Article in En | MEDLINE | ID: mdl-23694700

Subject(s)

Computational Biology/methods; Genes, Neoplasm; Melanoma/genetics; Models, Genetic; Mutation Rate; Gene Expression Profiling; Humans; Loss of Heterozygosity; Melanoma/metabolism; Mutation/genetics; Mutation/radiation effects; Tumor Cells, Cultured; Ultraviolet Rays

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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Computational Biology / Genes, Neoplasm / Mutation Rate / Melanoma / Models, Genetic Type of study: Diagnostic_studies / Prognostic_studies Limits: Humans Language: En Journal: IEEE Trans Nanobioscience Journal subject: BIOTECNOLOGIA Year: 2013 Document type: Article Affiliation country: United States

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