Uncovering signal transduction networks from high-throughput data by integer linear programming.

Nucleic Acids Research
Xing-Ming ZhaoKazuyuki Aihara

Abstract

Signal transduction is an important process that transmits signals from the outside of a cell to the inside to mediate sophisticated biological responses. Effective computational models to unravel such a process by taking advantage of high-throughput genomic and proteomic data are needed to understand the essential mechanisms underlying the signaling pathways. In this article, we propose a novel method for uncovering signal transduction networks (STNs) by integrating protein interaction with gene expression data. Specifically, we formulate STN identification problem as an integer linear programming (ILP) model, which can be actually solved by a relaxed linear programming algorithm and is flexible for handling various prior information without any restriction on the network structures. The numerical results on yeast MAPK signaling pathways demonstrate that the proposed ILP model is able to uncover STNs or pathways in an efficient and accurate manner. In particular, the prediction results are found to be in high agreement with current biological knowledge and available information in literature. In addition, the proposed model is simple to be interpreted and easy to be implemented even for a large-scale system.

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Citations

Sep 21, 2013·Nature Reviews. Genetics·Koyel MitraTrey Ideker
Mar 1, 2012·IET Systems Biology·Z-P LiuL Chen
Dec 29, 2010·Proceedings of the National Academy of Sciences of the United States of America·M Bailly-BechetR Zecchina
Mar 29, 2011·Computer Methods in Biomechanics and Biomedical Engineering·Yue HuangGuangshu Hu
Jun 27, 2013·Database : the Journal of Biological Databases and Curation·Xiaoping LiuXing-Ming Zhao
Nov 27, 2010·Nucleic Acids Research·Anthony GitterZiv Bar-Joseph
Jan 3, 2012·Nucleic Acids Research·Christina BackesHans-Peter Lenhof
Dec 15, 2010·BMC Bioinformatics·Gurkan BebekMark R Chance
May 25, 2012·BMC Bioinformatics·Yin-Ying WangXing-Ming Zhao
Sep 25, 2010·BMC Systems Biology·Zikai WuLuonan Chen
Jan 20, 2012·BMC Systems Biology·Liang-Chun ChenVon-Wun Soo
Oct 12, 2012·BMC Systems Biology·Ke-Jia XuXing-Ming Zhao
Aug 24, 2012·PLoS Computational Biology·Saket NavlakhaZiv Bar-Joseph
May 31, 2014·PLoS Computational Biology·Deborah ChasmanMark Craven
Jul 31, 2013·PloS One·Yuxuan HuDavid K Y Chiu
Apr 15, 2014·BMC Bioinformatics·Claudio SaccàAndrea Passerini
Apr 15, 2014·BioMed Research International·Shan LiXing-Ming Zhao
Sep 13, 2012·Journal of the American Medical Informatics Association : JAMIA·Zhenshu WenLuonan Chen
Sep 29, 2011·Current Opinion in Microbiology·Lore Cloots, Kathleen Marchal
Apr 2, 2016·Computational and Mathematical Methods in Medicine·Yun-Xia Zhang, Yan-Li Zhao
Sep 12, 2015·IEEE/ACM Transactions on Computational Biology and Bioinformatics· Young-Rae ChoGreg Speegle
Apr 27, 2011·IEEE/ACM Transactions on Computational Biology and Bioinformatics·Chun-Hou ZhengDe-Shuang Huang
Aug 6, 2015·IET Systems Biology·Fengyong YangGuangchen Wei
Oct 27, 2012·Asian Pacific Journal of Cancer Prevention : APJCP·Xiao-Hua Pan
Jun 17, 2014·Journal of Theoretical Biology·Guimin Qin, Xing-Ming Zhao
May 9, 2014·Computational and Mathematical Methods in Medicine·Wei KongYang Yang
Dec 7, 2014·Pathology Oncology Research : POR·Xiaodong ZhouTianlin He
Dec 17, 2014·Bioinformatics·Xing-Ming ZhaoLuonan Chen
Jul 23, 2016·IET Systems Biology·Zhenshen BaoWenbin Liu
Apr 3, 2009·Journal of Bioinformatics and Computational Biology·Xing-Ming ZhaoKazuyuki Aihara
Dec 30, 2016·Bioinformatics·Gui-Min QinXing-Ming Zhao

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Datasets Mentioned

BETA
GSE28

Methods Mentioned

BETA
GTPase

Software Mentioned

Pathfinder
ILP
DFS
DIP
MATLAB
Netsearch

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