PathMiner: predicting metabolic pathways by heuristic search | Zendy

D. C. McShan | Zendy; Shaoqi Rao | Zendy; Imran Shah | Zendy

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PathMiner: predicting metabolic pathways by heuristic search

Author(s) -

D. C. McShan,

Shaoqi Rao,

Imran Shah

Publication year - 2003

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btg217

Subject(s) - heuristic , computer science , metabolic pathway , computational biology , machine learning , artificial intelligence , biology , gene , genetics

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.

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