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Bioinformatics Vol. 19 no. 13 2003
Pages 1692-1698
© 2003 Oxford University Press

PathMiner: predicting metabolic pathways by heuristic search

D.C. McShan , S. Rao and I. Shah *

School of Medicine, University of Colorado, 4200 East Ninth Avenue, C-245 Denver, Colorado 80262, USA

Received on August 2, 2002 ; revised on February 19, 2003 ; accepted on March 19, 2003

Motivation: Automated methods for biochemical pathway inference are becoming increasingly important for understanding biological processes in living and synthetic systems. With the availability of data on complete genomes and increasing information about enzyme-catalyzed biochemistry it is becoming feasible to approach this problem computationally. In this paper we present PathMiner, a system for automatic metabolic pathway inference. PathMiner predicts metabolic routes by reasoning over transformations using chemical and biological information.

Results: We build a biochemical state-space using data from known enzyme-catalyzed transformations in Ligand, including, 2917 unique transformations between 3890 different compounds. To predict metabolic pathways we explore this state-space by developing an informed search algorithm. For this purpose we develop a chemically motivated heuristic to guide the search. Since the algorithm does not depend on predefined pathways, it can efficiently identify plausible routes using known biochemical transformations.

Availability: The system is available for testing at http://pathminer.uchsc.edu

Contact: imran.shah{at}uchsc.edu

* To whom correspondence should be addressed.


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