Institution:山东大学数学学院

Title of Paper:MaxMIF: a new method for identifying cancer driver genes through effective data integration

Journal:Advanced Science

Summary:Identification of a few cancer driver mutation genes from a much larger number of passenger mutation genes in cancer samples remains a highly challenging task. Here, a novel method for distinguishing the driver genes from the passenger genes by effective integration of somatic mutation data and molecular interaction data using a maximal mutational impact function (MaxMIF) is presented. When evaluated on six somatic mutation datasets of Pan‐Cancer and 19 datasets of different cancer types from TCGA, MaxMIF almost always significantly outperforms all the existing state‐of‐the‐art methods in ...

First Author:Hou, Y.

Correspondence Author:Li*, G.,Su*, Z

All the Authors:Gao, B.

Indexed by:Journal paper

Discipline:Natural Science

First-Level Discipline:Mathematics

Document Type:J

Volume:5

Issue:9

Translation or Not:No

Date of Publication:2018-07

Included Journals:SCI

Release Time:2019-07-10