Paper Title:
Design and Construction of a Yeast Gene Bayesian Regulatory Network
  Abstract

At present, biological data provide possibility to further data analysis data, improving deep understanding on complicated regulatory model. Thanks to the study of model organism yeast and the construction of its gene regulatory network, we can improve the diagnosis and treatment level of the human polygene hereditary diseases which are similar to yeast genes. Among a variety of gene regulatory network models, the one constructed by Bayesian Network corresponds to Biology's reality most. So we choose Bayesian Network to construct yeast gene regulatory network, of which process involves Bayesian Network structure learning and parameter learning. We gather and integrate the yeast data, by which we determine the network nodes. We learn the structure using MMHC algorithm, and use the simulated annealing algorithm to rating search so that we can get the best solution. Finally we use Bayesian algorithm or MLE algorithm to learn and determine the parameter. With the help of this regulatory network, researchers are able to have more acquaintance with the complex regulatory relationships in the gene regulatory network.

  Info
Periodical
Advanced Materials Research (Volumes 383-390)
Chapter
Chapter 16: Biomedical Manufacturing
Edited by
Wu Fan
Pages
3980-3985
DOI
10.4028/www.scientific.net/AMR.383-390.3980
Citation
M. C. Zhou, F. Zhu, "Design and Construction of a Yeast Gene Bayesian Regulatory Network", Advanced Materials Research, Vols. 383-390, pp. 3980-3985, 2012
Online since
November 2011
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Price
$32.00
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