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