SRI International (SRI) proposes to collect data on the genes and metabolism of Escherichia coli, and to encode these data in a computer database that is accessible to all scientists. We will compile data information on intermediary metabolism from the biological literature. A collaborator will provide us with a database on the genes of E coli. We will encode the genetic and metabolic information in database form. In addition, SRI will implement a graphical user interface to the metabolic data, and integrate the metabolic graphical interface with a graphical user interface for genetic data developed at the Jackson Laboratory. The resulting program will allow scientist to access genetic and metabolic data in a graphical, user-friendly manner. In addition, we will distribute the database (to be called EcoCyc) in several different database formats so that scientists can access the data in other convenient forms. The EcoCyc database will describe every reaction of the intermediary metabolism of E coli, listing the reaction equation, its EC number, cofactors, activators, and inhibitors. EcoCyc will also describe the enzymes that catalyze these reactions, listing their molecular weight, subunit composition, encoding genes, and cross reference to protein and nucleic-acid sequence databases. For each gene EcoCyc will list the gene name, and the starting and ending position of the gene within the E coli chromosome. Literature citations will be included in all the preceding items. EcoCyc will be valuable as a reference source for many scientists. Molecular biologists and biotechnologists designing a cloning project will have instant access to the best current information on map locations, identity of linked genes and their functions, lists of available clones, and locations of pertinent restriction sites. Microbial geneticists who work with bacteria other than E coli may find facile access to E coli data useful as a point of reference for gene functions, as well as for similarities and differences of gene-enzyme relationships in other organisms. Molecular evolutionists interested in ancestral relationships among genes, enzymes and pathways could use the database to search for examples of duplication and divergence. EcoCyc will also be useful to scientists who perform quantitative simulations of metabolic pathways, and to those who design variants of biochemical pathways for industrial applications.
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