SRI International and a group of collaborators propose to further develop the Escherichia coli EcoCyc database (DB). EcoCyc is and will continue to be freely and openly available, and is accessible to scientists through the Internet, as downloadable data files, and as a downloadable software application. Scientists from multiple disciplines make wide use of EcoCyc; it has been cited 2,700 times, and 170,000 visitors query the EcoCyc website each year. It serves as a general reference source on E. coli for experimental biologists, and is particularly useful for the analysis of functional-genomics experiments. The DB serves computational biologists who are undertaking global studies of E. coli; metabolic engineers who are developing new methods for chemicals production including biofuels; and researchers and bioinformaticists who are using EcoCyc as the gold-standard dataset to develop new computational methods, including the prediction of operons, promoters, and protein functional linkages. Educators also use the DB. We will update EcoCyc in an ongoing fashion to reflect new information about the genes, metabolic pathways, and regulatory interactions of these important model organisms. Information will be integrated from the biomed- ical literature and from large-scale experiments, such as data on gene essentiality, on nutrients supporting growth, and on protein interactions. We will continue a comprehensive and ongoing effort to refine steady-state metabolic network models of these organisms by validating model predictions against many conditions of growth and non- growth for wildtype and knock- out strains. The resulting models will have applications in anti-microbial drug discovery and metabolic engineering, and the model development process will leads to many improvements in the underlying DBs. The project will also expand the PTools software used to query and analyze EcoCyc and the larger BioCyc DB collection, thus enabling web-based execution of metabolic models, and the development of new methods for the analysis of multi-omics data.
Escherichia coli is the most thoroughly studied bacterium on earth; therefore, a computer knowledge base that integrates experimental findings for this organism from thousands of scientific publications is a valuable and cost- effective resource for science and education. The comprehensive knowledge and computational tools available through EcoCyc accelerate the research of scientists who use this organism to develop biofuels, scientists who study related pathogenic bacteria, and scientists who work with the bacteria comprising the human microbiome
| Caspi, Ron; Billington, Richard; Fulcher, Carol A et al. (2018) The MetaCyc database of metabolic pathways and enzymes. Nucleic Acids Res 46:D633-D639 |
| Karp, Peter D; Billington, Richard; Caspi, Ron et al. (2017) The BioCyc collection of microbial genomes and metabolic pathways. Brief Bioinform : |
| Keseler, Ingrid M; Mackie, Amanda; Santos-Zavaleta, Alberto et al. (2017) The EcoCyc database: reflecting new knowledge about Escherichia coli K-12. Nucleic Acids Res 45:D543-D550 |
| Karp, Peter D; Latendresse, Mario; Paley, Suzanne M et al. (2016) Pathway Tools version 19.0 update: software for pathway/genome informatics and systems biology. Brief Bioinform 17:877-90 |
| Karp, Peter D (2016) Crowd-sourcing and author submission as alternatives to professional curation. Database (Oxford) 2016: |
| Karp, Peter D (2016) How much does curation cost? Database (Oxford) 2016: |
| Gama-Castro, Socorro; Salgado, Heladia; Santos-Zavaleta, Alberto et al. (2016) RegulonDB version 9.0: high-level integration of gene regulation, coexpression, motif clustering and beyond. Nucleic Acids Res 44:D133-43 |
| Caspi, Ron; Billington, Richard; Ferrer, Luciana et al. (2016) The MetaCyc database of metabolic pathways and enzymes and the BioCyc collection of pathway/genome databases. Nucleic Acids Res 44:D471-80 |
| Karp, Peter D (2016) Can we replace curation with information extraction software? Database (Oxford) 2016: |
| Weaver, Daniel S; Keseler, Ingrid M; Mackie, Amanda et al. (2014) A genome-scale metabolic flux model of Escherichia coli K-12 derived from the EcoCyc database. BMC Syst Biol 8:79 |
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