Evaluation and integration of cancer gene classifiers: identification and ranking of plausible drivers.
Ontology highlight
ABSTRACT:
SUBMITTER: Liu Y
PROVIDER: S-EPMC4650817 | biostudies-other | 2015 May
REPOSITORIES: biostudies-other
Publications
Evaluation and integration of cancer gene classifiers: identification and ranking of plausible drivers.
Liu Yang Y Tian Feng F Hu Zhenjun Z DeLisi Charles C
Scientific reports 20150511
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 available, and apply it to breast and ovarian cancer. In particular we find the following: (1 ...[more]
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