The completion of the genome sequence for an organism such as a disease-causing bacterium marks the start of a new era of accelerated research on that organism. The huge quantity of data and knowledge defined by the genome sequence, and by the large number of past and future experimental endings for the organism, requires the use of a database to act as a central repository for information about the genome, the biochemical network, and the regulatory processes of that organism. In the past, such organism-specific databases, also called Model-Organism Databases (MODs), were each created with custom-developed software tools. Because of the many common requirements of these projects, the cost of creating custom software, and the database incompatibility that results from using custom software, it is more effective to reuse a common software environment across many MOD projects. The Pathway Tools software is a robust and comprehensive system for the construction of MODs. Pathway Tools enables communities of scientists to create, query, visualize, analyze, and publish MODs on the Web. Pathway Tools provides support for a large number of bioinformatics data types including genome maps, genes, operons, RNAs, proteins, chemical compounds, biochemical reactions, metabolic pathways, and regulatory interactions. Pathway Tools is a mature and production-quality software environment that has been used by more than 75 groups outside SRI to create more than 250 MODs. We propose to further develop Pathway Tools to edit and display signaling pathways, to better display and interrogate cellular regulatory networks, to make its genome-scale tools for display of cellular networks more functional through the Web, and to enhance Pathway Tools representations of cellular architectures to more accurately model complex cell types. We propose to provide support services for the large and growing user community for Pathway Tools, to maintain quality documentation for the software, and to create two thoroughly tested releases of the software per year. 7

Public Health Relevance

will generate software tools that lead to fuller realization of the value of genome sequence data. This software enables the creation of central database repositories of genome data and data on cellular networks for disease-causing bacteria and experimental model organisms such as the laboratory mouse. The software allows researchers to access the most up-to-date information about those organisms using intuitive querying tools, and provides scientific visualization capabilities that aid scientists in more quickly understanding large complex collections of data.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
5R01GM075742-08
Application #
7792348
Study Section
Special Emphasis Panel (ZRG1-BST-Q (02))
Program Officer
Anderson, James J
Project Start
2005-04-01
Project End
2012-03-31
Budget Start
2010-04-01
Budget End
2012-03-31
Support Year
8
Fiscal Year
2010
Total Cost
$649,906
Indirect Cost
Name
Sri International
Department
Type
DUNS #
009232752
City
Menlo Park
State
CA
Country
United States
Zip Code
94025
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Paley, Suzanne; Krummenacker, Markus; Karp, Peter D (2016) Representation and inference of cellular architecture for metabolic reconstruction and modeling. Bioinformatics 32:1074-9
Karp, Peter D; Billington, Richard; Holland, Timothy A et al. (2015) Computational Metabolomics Operations at BioCyc.org. Metabolites 5:291-310
Dingerdissen, Hayley; Weaver, Daniel S; Karp, Peter D et al. (2014) A framework for application of metabolic modeling in yeast to predict the effects of nsSNV in human orthologs. Biol Direct 9:9
Latendresse, Mario (2014) Efficiently gap-filling reaction networks. BMC Bioinformatics 15:225
Hanson, Niels W; Konwar, Kishori M; Hawley, Alyse K et al. (2014) Metabolic pathways for the whole community. BMC Genomics 15:619
Caspi, Ron; Altman, Tomer; Billington, Richard et al. (2014) The MetaCyc database of metabolic pathways and enzymes and the BioCyc collection of Pathway/Genome Databases. Nucleic Acids Res 42:D459-71
Caspi, Ron; Dreher, Kate; Karp, Peter D (2013) The challenge of constructing, classifying, and representing metabolic pathways. FEMS Microbiol Lett 345:85-93

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