DocumentCode :
3519850
Title :
Partial Order-Based Bayesian Network Learning Algorithm for Estimating Gene Networks
Author :
Numata, Kazuyuki ; Imoto, Seiya ; Miyano, Satoru
Author_Institution :
Human Genome Center, Univ. of Tokyo, Tokyo
fYear :
2008
fDate :
3-5 Nov. 2008
Firstpage :
357
Lastpage :
360
Abstract :
For learning Bayesian network structure from data, order-based algorithms such as K2 algorithm are widely used.In this paper, we consider a problem of constructing the order of nodes in such algorithms based on prior knowledge of gene networks. However, in many cases the prior knowledge is given as partial order of genes and we need to extend the order-based algorithm to partial order-based one. By extending our prior work we propose an efficient partial order-based algorithm for estimating gene networks based on Bayesian networks. The computational complexity of the proposed algorithm is shown.
Keywords :
belief networks; bioinformatics; genetics; learning (artificial intelligence); Bayesian network learning algorithm; K2 algorithm; gene networks estimation; partial order; Bayesian methods; Bioinformatics; Clustering algorithms; Computational Intelligence Society; Computational complexity; Gene expression; Genomics; Graphical models; Humans; Proteins; Bayesian network structure learning; gene regulatory networks;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Bioinformatics and Biomedicine, 2008. BIBM '08. IEEE International Conference on
Conference_Location :
Philadelphia, PA
Print_ISBN :
978-0-7695-3452-7
Type :
conf
DOI :
10.1109/BIBM.2008.85
Filename :
4684919
Link To Document :
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