NDLI: Modeling Large-Scale Gene Regulatory Networks using Gene Ontology-Based Clustering and Dynamic Bayesian Networks

Content Provider	IEEE Xplore Digital Library
Author	Yavari, F. Towhidkhah, F. Gharibzadeh, Sh. Khanteymoori, A.R. Homayounpour, M.M.
Copyright Year	2008
Description	Author affiliation: Biomed. Eng. Fac., Amirkabir Univ. of Technol., Tehran (Yavari, F.; Towhidkhah, F.; Gharibzadeh, Sh.)
Abstract	For understanding the function of an organism, it is necessary to know "which", "how fast", and "when" the genes are expressed. A gene regulatory network represents how and when the genes interact with each other. Using genetic network modeling, it is possible to explain the cell functions at molecular level. DNA microarrays can measure the expression levels of thousands of genes simultaneously. Most of methodologies have proposed so far for modeling gene networks from microarray data take into account only a small number of genes. In this paper, a two steps method is proposed that can model large-scale Gene Regulatory Networks using time series microarray data. Firstly, genes are clustered based on existing biological knowledge (Gene Ontology annotations) and then a higher-order Markov dynamic Bayesian network is applied in order to model causal relationships between genes in each cluster. Finally the learned subnetworks are integrated to make a global network. This method is applied to reconstruct the regulatory network of 75 yeast genes from cell cycle gene expression dataset collected by Spellman et al. (1998). Comparing the results with the KEGG pathway map, indicates that this approach is capable of finding 31% of true relationships between genes (69% if directionality and time delay is not considered).
Starting Page	297
Ending Page	300
File Size	241869
Page Count	4
File Format	PDF
ISBN	9781424417476
DOI	10.1109/ICBBE.2008.76
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-05-16
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Fungi Bayesian methods Biological system modeling Delay effects DNA Ontologies Genetics Organisms Large-scale systems Gene expression
Content Type	Text
Resource Type	Article

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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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