Article
Evaluation and integration of cancer gene classifiers: identification and ranking of plausible drivers.
Scientific reports - 11 May 2015
Liu Yang, Tian Feng, Hu Zhenjun, DeLisi Charles
Abstract excerpt
The number of mutated genes in cancer cells is far larger than the number of mutations that drive cancer. The difficulty this creates for identifying relevant alterations has stimulated the development of various computational approaches to distinguishing drivers from bystanders. We develop and apply an ensemble classifier (EC) machine learning method, which integrates 10 classifiers that are publically...
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