Article Abstract

	Title:	Cellular function prediction and biological pathway discovery in Arabidopsis thaliana using microarray data
	Author:	Trupti Joshi, Yu Chen, Nickolai N. Alexandrov, Dong Xu
	Address:	Digital Biology Laboratory, Department of Computer Science, University of Missouri-Columbia, Columbia, MO, USA. ' Digital Biology Laboratory, Department of Computer Science, University of Missouri-Columbia, Columbia, MO, USA; UT-ORNL Graduate School of Genome Science and Technology, Oak Ridge, TN, USA. ' Ceres, Inc., 1535 Rancho Conejo Blvd., Thousand Oaks, CA, USA. ' Digital Biology Laboratory, Department of Computer Science, University of Missouri-Columbia, Columbia, MO, USA; UT-ORNL Graduate School of Genome Science and Technology, Oak Ridge, TN, USA
	Journal:	International Journal of Bioinformatics Research and Applications 2005 - Vol. 1, No.3  pp. 335 - 350
	Abstract:	Determination of protein function and biological pathway is one of the most challenging problems in the post-genomic era. To address this challenge, we have developed a new integrated probabilistic method for cellular function prediction using microarray gene expression profiles, in conjunction with predicted protein-protein interactions and annotations of known proteins. 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 prediction of hypothetical genes in Arabidopsis. We have also extended our method using Dijkstra's algorithm to identify the components and topology of signaling pathway of phosphatidic acid as a second messenger in Arabidopsis.
	Keywords:	cellular function prediction; microarray gene expression profiles; protein-protein interactions; high-throughput data; Arabidopsis thaliana; biological pathways; bioinformatics; gene ontology; protein function.
	DOI:	10.1504/IJBRA.2005.007910
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