Identification and Analysis of Driver Missense Mutations Using Rotation Forest with Feature Selection

Identification and Analysis of Driver Missense Mutations Using Rotation Forest with Feature Selection

Identifying cancer-associated mutations (driver mutations) is critical for understanding the cellular function of cancer genome that leads to activation of oncogenes or inactivation of tumor suppressor genes. Many approaches are proposed which use supervised machine learning techniques for predictio...

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Bibliographic Details
Main Authors:	Xiuquan Du, Jiaxing Cheng
Format:	Article
Language:	English
Published:	Hindawi Limited 2014-01-01
Series:	BioMed Research International
Online Access:	http://dx.doi.org/10.1155/2014/905951

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