NDLI: A Bayesian network based algorithm for gene regulatory network reconstruction

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A Bayesian network based algorithm for gene regulatory network reconstruction

Content Provider	IEEE Xplore Digital Library
Author	Bo Yang Junying Zhang Junliang Shang Aimin Li
Copyright Year	2011
Description	Author affiliation: School of Computer Science and Technology, Xidian University, Xi'an, P. R. China (Bo Yang; Junying Zhang; Junliang Shang; Aimin Li)
Abstract	Bayesian network (BN) modeling is a commonly used method for constructing gene regulatory networks from gene microarray data. Learning the structures of BNs from data is of significant importance in applications of various fields. In this paper, we propose a Sparse Graph Search (SGS) algorithm that not only reduces BN computation times significantly but also obtains optimal network constructions by using hybrid approach that combines search-and-score with constraint-based method. The algorithm is applied to several sets of benchmark networks and is shown to outperform PC and TPDA algorithms.
Starting Page	1
Ending Page	4
File Size	647919
Page Count	4
File Format	PDF
ISBN	9781457708930
e-ISBN	9781457708947
DOI	10.1109/ICSPCC.2011.6061811
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-09-14
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Learning systems Algorithm design and analysis Learning algorithms Machine learning algorithms Bayesian methods Bayesian Network Machine learning Markov processes Skeleton Gene expression regulation Bioinformatics
Content Type	Text
Resource Type	Article

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