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GSGS: A Computational Approach to Reconstruct Signaling Pathway Structures from Gene Sets

Content Provider	IEEE Xplore Digital Library
Author	Acharya, L. Judeh, T. Zhansheng Duan Rabbat, M. Dongxiao Zhu
Copyright Year	2004
Abstract	Reconstruction of signaling pathway structures is essential to decipher complex regulatory relationships in living cells. The existing computational approaches often rely on unrealistic biological assumptions and do not explicitly consider signal transduction mechanisms. Signal transduction events refer to linear cascades of reactions from the cell surface to the nucleus and characterize a signaling pathway. In this paper, we propose a novel approach, Gene Set Gibbs Sampling (GSGS), to reverse engineer signaling pathway structures from gene sets related to the pathways. We hypothesize that signaling pathways are structurally an ensemble of overlapping linear signal transduction events which we encode as Information Flows (IFs). We infer signaling pathway structures from gene sets, referred to as Information Flow Gene Sets (IFGSs), corresponding to these events. Thus, an IFGS only reflects which genes appear in the underlying IF but not their ordering. GSGS offers a Gibbs sampling like procedure to reconstruct the underlying signaling pathway structure by sequentially inferring IFs from the overlapping IFGSs related to the pathway. In the proof-of-concept studies, our approach is shown to outperform the existing state-of-the-art network inference approaches using both continuous and discrete data generated from benchmark networks in the DREAM initiative. We perform a comprehensive sensitivity analysis to assess the robustness of our approach. Finally, we implement GSGS to reconstruct signaling mechanisms in breast cancer cells.
Sponsorship	IEEE Computer Society
Page Count	13
File Size	1571655
Starting Page	438
Ending Page	450
File Format	PDF
ISSN	15455963
Volume Number	9
Issue Number	2
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-01-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Bioinformatics Educational institutions Computational biology Joints USA Councils Computer science Aerospace electronics signal transduction. Gene sets Gibbs sampling signaling pathways
Content Type	Text
Resource Type	Article
Subject	Applied Mathematics Genetics Biotechnology

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