Deciphering oncogenic drivers: from single genes to integrated pathways
作者： J. Chen , M. Sun , B. Shen
DOI: 10.1093/BIB/BBU039
关键词: Extant taxon 、 Cancer 、 Computational biology 、 Cancer mutations 、 Genome 、 Gene 、 Mutation (genetic algorithm) 、 Function (biology) 、 Biology
摘要: Technological advances in next-generation sequencing have uncovered a wide spectrum of aberrations cancer genomes. The extreme diversity mutations necessitates computational approaches to differentiate between the 'drivers' with vital function progression and those nonfunctional 'passengers'. Although individual driver are routinely identified, mutational profiles different tumors highly heterogeneous. There is growing consensus that pathways rather than single genes primary target mutations. Here we review extant bioinformatics identifying oncogenic drivers at levels, highlighting strategies for discovering networks from mutation data. These will help reduce complexity, thus providing simplified picture cancer.
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