NDLI: Bayesian network approach to understand regulation of biological processes in cyanobacteria

Content Provider	IEEE Xplore Digital Library
Author	Elvitigala, T.R. Singh, A.K. Pakrasi, H.B. Ghosh, B.K.
Copyright Year	2009
Description	Author affiliation: Department of Mathematics and Statistics, Texas Tech University, Lubbock, USA (Ghosh, B.K.) \|\| Department of Biology, Washington University in St Louis, MO, USA (Singh, A.K.; Pakrasi, H.B.) \|\| Department of Electrical and Systems Engineering, Washington University in St Louis, MO, USA (Elvitigala, T.R.)
Abstract	Bayesian networks have extensively been used in numerous fields including artificial intelligence, decision theory and control. Its ability to utilize noisy and missing data makes it a good candidate to study biological systems. In this paper we propose the use of Bayesian network approach to study cellular response of cyanobacteria. We discuss how to combine individual gene expressions, obtained from microarrays generated using different platforms, to get biological process level behaviors. Biological processes carry more information towards understanding overall cell behavior. We then discuss several approaches available for identifying the structure of a Bayesian network and derive corresponding system level regulatory network for cyanobacterium, Synechocystis sp. PCC 6803. We discuss a method to quantify the strengths of the associations between different processes. The resultant network is used to simulate some of the experimental conditions and the responses of the network under those conditions are inferred. We show that these inferences agree with the observations made in the original experiments. Finally, we discuss how these type of networks could be helpful in making decisions on controlling the cellular activities so that the desired behaviors are achieved.
Starting Page	3739
Ending Page	3744
File Size	1887091
Page Count	6
File Format	PDF
ISBN	9781424438716
ISSN	01912216
DOI	10.1109/CDC.2009.5399570
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-12-15
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Bayesian methods Biological processes Biological systems Cellular networks Systems biology Artificial intelligence Decision theory Gene expression Cells (biology) Biological system modeling
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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