By Topic

Cellular function prediction and biological pathway discovery in Arabidopsis thaliana using microarray data

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)
T. Joshi ; Dept. of Comput. Sci., Missouri-Columbia Univ., Columbia, MO, USA ; Y. Chen ; N. Alexandrov ; D. Xu

We have developed a new integrated probabilistic method for cellular function prediction by using microarray gene expression profiles, in conjunction with predicted protein-protein interactions and annotations of known proteins through an integrative statistical model. Our approach is based on a novel assessment for the relationship between correlation of two genes' expression profiles and their functional relationship in terms of the gene ontology (GO) hierarchy. We applied the method for function predictions of hypothetical genes in Arabidopsis. We have also extended our computational method using Dijkstra's algorithm to identify the components and topology of a pathway, and we applied it for predicting the signaling pathway of phosphatidic acid as a second messenger in Arabidopsis.

Published in:

Engineering in Medicine and Biology Society, 2004. IEMBS '04. 26th Annual International Conference of the IEEE  (Volume:2 )

Date of Conference:

1-5 Sept. 2004