The full text of this article
Improved Bayesian Network inference using relaxed gene ordering
by Dongxiao Zhu, Hua Li
International Journal of Data Mining and Bioinformatics (IJDMB), Vol. 4, No. 1, 2010
Abstract: Bayesian Networks (BNs) have become one of the most powerful means of reconstructing signalling pathways in silico. Excessive computational loads limit the applications of BNs to learn larger sized network structures. Recent bioinformatics research found that signalling pathways are likely hierarchically organised. Genes resident in hierarchical layers constitute biological constraint, which can be readily used by BN structural learning algorithms to substantially reduce the computational load. We propose a constrained BN structural learning algorithm that solves the NP-complete computational problem in a heuristic manner. We demonstrate the utility of our algorithm in constructing two important signalling pathways in S. cerevisiae.
Online publication date: Thu, 14-Jan-2010
is only available to individual subscribers or to users at subscribing institutions.
Go to Inderscience Online Journals to access the Full Text of this article.
Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.
Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Data Mining and Bioinformatics (IJDMB):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable).
See our Orders page to subscribe.
If you still need assistance, please email email@example.com