By Topic

A Bayesian network based algorithm for gene regulatory network reconstruction

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Bo Yang ; School of Computer Science and Technology, Xidian University, Xi'an, P. R. China ; Junying Zhang ; Junliang Shang ; Aimin Li

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.

Published in:

Signal Processing, Communications and Computing (ICSPCC), 2011 IEEE International Conference on

Date of Conference:

14-16 Sept. 2011