DocumentCode :
35523
Title :
Mining gene link information for survival pathway hunting
Author :
Gao-Jian Jing ; Zirui Zhang ; Hong-Qiang Wang ; Hong-Mei Zheng
Author_Institution :
Machine Intell. & Comput. Biol. Lab., Inst. of Intell. Machines, Hefei, China
Volume :
9
Issue :
4
fYear :
2015
fDate :
8 2015
Firstpage :
147
Lastpage :
154
Abstract :
This study proposes a gene link-based method for survival time-related pathway hunting. In this method, the authors incorporate gene link information to estimate how a pathway is associated with cancer patient´s survival time. Specifically, a gene link-based Cox proportional hazard model (Link-Cox) is established, in which two linked genes are considered together to represent a link variable and the association of the link with survival time is assessed using Cox proportional hazard model. On the basis of the Link-Cox model, the authors formulate a new statistic for measuring the association of a pathway with survival time of cancer patients, referred to as pathway survival score (PSS), by summarising survival significance over all the gene links in the pathway, and devise a permutation test to test the significance of an observed PSS. To evaluate the proposed method, the authors applied it to simulation data and two publicly available real-world gene expression data sets. Extensive comparisons with previous methods show the effectiveness and efficiency of the proposed method for survival pathway hunting.
Keywords :
bioinformatics; cancer; genomics; physiological models; cancer patient survival time; gene link-based Cox proportional hazard model; gene link-based method; pathway survival score; permutation test; survival time-related pathway hunting;
fLanguage :
English
Journal_Title :
Systems Biology, IET
Publisher :
iet
ISSN :
1751-8849
Type :
jour
DOI :
10.1049/iet-syb.2014.0048
Filename :
7181751
Link To Document :
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