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Unsupervised detection of cancer driver mutations with parsimony-guided learning

Methods are needed to reliably prioritize biologically active driver mutations over inactive passengers in high-throughput cancer sequencing datasets. We present ParsSNP, an unsupervised functional impact predictor that is guided by parsimony. ParsSNP uses an expectation-maximization framework to fi...

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Detalhes bibliográficos
Publicado no:Nat Genet
Main Authors: Kumar, Runjun D., Swamidass, S. Joshua, Bose, Ron
Formato: Artigo
Idioma:Inglês
Publicado em: 2016
Assuntos:
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC5328615/
https://ncbi.nlm.nih.gov/pubmed/27618449
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1038/ng.3658
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