NDLI: Detecting aberrant signal transduction pathways from high-throughput data using GIST algorithm

Content Provider	IEEE Xplore Digital Library
Author	Jinghua Gu Jianhua Xuan Chen Wang Li Chen Tian-Li Wang Ie-Ming Shih
Copyright Year	2012
Description	Author affiliation: The Bradley Dept. of Electrical & Computer Engineering, Virginia Tech, Arlington, 22203, USA (Jinghua Gu; Jianhua Xuan; Chen Wang) \|\| Department of Pathology, Johns Hopkins Medical Institutions, Baltimore, MD 21231, USA (Li Chen; Tian-Li Wang; Ie-Ming Shih)
Abstract	It is biologically important to integrate high-throughput data to identify aberrant signal transduction pathways in cancer research. The high-throughput data acquired from The Cancer Genome Atlas (TCGA) Project offer a comprehensive picture of the genomic and transcriptional changes across hundreds of tumor samples. In this paper we propose a novel method, namely Gibbs sampler to Infer Signal Transduction pathways (GIST), to detect aberrant pathways that are highly associated with biological phenotypes or clinical information. GIST endeavors to estimate the edge probability by using a Markov Chain Monte Carlo (MCMC) method (i.e., a Gibbs sampling strategy). Through the sampling process, GIST is able to infer the correct signal transduction direction because the sampled edge probabilities are jointly determined by gene expression data and network topology. We first tested the efficacy of the GIST algorithm on yeast data and successfully uncovered several biologically meaningful signaling pathways. A case study on TCGA ovarian cancer data was further designed, aiming to unravel diverse signaling pathways associated with the development of ovarian cancer. The experimental results demonstrated the feasibility of applying GIST to identify and prioritize important signaling pathways in ovarian cancer for further biological validation.
Starting Page	267
Ending Page	274
File Size	1656696
Page Count	8
File Format	PDF
ISBN	9781467311908
e-ISBN	9781467311915
DOI	10.1109/CIBCB.2012.6217240
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-05-09
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Proteins Gene expression Cancer Vectors Correlation Encoding gene expression signal transduction pathway Markov chain Mote Carlo Gibbs sampling protein-protein interaction
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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