
Peter Karp
Technical Director, Artificial Intelligence Center
Peter Karp, Ph.D., Technical Director of the Bioinformatics Research Group at SRI International, works in the interdisciplinary field of bioinformatics, which develops computer-science methods for managing and analyzing the burgeoning quantities of biological data and knowledge.
Karp has been a pioneer in metabolic-pathway bioinformatics. His group has developed a metabolic-pathway database called EcoCyc that charts the complete biochemical factory within an Escherichia coli cell. His group has also developed algorithms for visualization of metabolic networks, for predicting anti-bacterial drug targets within metabolic networks, and for predicting the metabolic pathways of an organism whose genome has been sequenced. The latter algorithm has been applied to thousands of organisms to produce the BioCyc database collection.
Karp has authored more than 190 publications in computer science and bioinformatics. He is an SRI Fellow, a Fellow of the International Society for Computational Biology, and a Fellow of the American Association for the Advancement of Science.
Recent publications
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BioCyc: Metabolic Pathway Databases and Informatics Tools
This article describes a coordinated set of bioinformatics databases and software tools designed to solve multiple problems faced by metabolic engineers and microbiologists related to metabolic pathways.
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Reviewing Knowledgebase and Database Grant Proposals in the Life Sciences: The Role of Innovation
This article offers thoughts on reviewing grant proposals for biological knowledgebases and databases (KDs) in the hope of aiding grant reviewers and applicants in addressing the issue of innovation.
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Pathway Tools Management of Pathway/Genome Data for Microbial Communities
The Pathway Tools software provides a suite of capabilities for storing and analyzing collections of genomic and metabolic information.
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Metabolic Modeling with MetaFlux
The MetaFlux software supports creating, executing, and solving quantitative metabolic flux models using flux balance analysis (FBA).
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The EcoCyc Database in 2021
This article highlights recent improvements to the curated data in the areas of metabolism, transport, DNA repair, and regulation of gene expression.
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The BioCyc Metabolic Network Explorer
The Metabolic Network Explorer is a new addition to the BioCyc.org website and the Pathway Tools software suite that supports the interactive exploration of metabolic networks.