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

Trupti Joshi; Yu Chen; Nickolai Alexandrov; Dong Xu

doi:10.1109/IEMBS.2004.1403820

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

Conf Proc IEEE Eng Med Biol Soc. 2004:2004:2881-4. doi: 10.1109/IEMBS.2004.1403820.

Authors

Trupti Joshi¹, Yu Chen, Nickolai Alexandrov, Dong Xu

Affiliation

¹ Dept. of Comput. Sci., Missouri-Columbia Univ., Columbia, MO, USA.

PMID: 17270879
DOI: 10.1109/IEMBS.2004.1403820

Abstract

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.