EcoCyc: a comprehensive database of Escherichia coli biology.

EcoCyc (http://EcoCyc.org) is a comprehensive model organism database for Escherichia coli K-12 MG1655. From the scientific literature, EcoCyc captures the functions of individual E. coli gene products; their regulation at the transcriptional, post-transcriptional and protein level; and their organization into operons, complexes and pathways. EcoCyc users can search and browse the information in multiple ways. Recent improvements to the EcoCyc Web interface include combined gene/protein pages and a Regulation Summary Diagram displaying a graphical overview of all known regulatory inputs to gene expression and protein activity. The graphical representation of signal transduction pathways has been updated, and the cellular and regulatory overviews were enhanced with new functionality. A specialized undergraduate teaching resource using EcoCyc is being developed.

The MetaCyc database of metabolic pathways and enzymes and the BioCyc collection of pathway/genome databases.

The MetaCyc database (MetaCyc.org) is a comprehensive and freely accessible resource for metabolic pathways and enzymes from all domains of life. The pathways in MetaCyc are experimentally determined, small-molecule metabolic pathways and are curated from the primary scientific literature. With more than 1400 pathways, MetaCyc is the largest collection of metabolic pathways currently available. Pathways reactions are linked to one or more well-characterized enzymes, and both pathways and enzymes are annotated with reviews, evidence codes, and literature citations. BioCyc (BioCyc.org) is a collection of more than 500 organism-specific Pathway/Genome Databases (PGDBs). Each BioCyc PGDB contains the full genome and predicted metabolic network of one organism. The network, which is predicted by the Pathway Tools software using MetaCyc as a reference, consists of metabolites, enzymes, reactions and metabolic pathways. BioCyc PGDBs also contain additional features, such as predicted operons, transport systems, and pathway hole-fillers. The BioCyc Web site offers several tools for the analysis of the PGDBs, including Omics Viewers that enable visualization of omics datasets on two different genome-scale diagrams and tools for comparative analysis. The BioCyc PGDBs generated by SRI are offered for adoption by any party interested in curation of metabolic, regulatory, and genome-related information about an organism.

Pathway Tools version 13.0: integrated software for pathway/genome informatics and systems biology.

Pathway Tools is a production-quality software environment for creating a type of model-organism database called a Pathway/Genome Database (PGDB). A PGDB such as EcoCyc integrates the evolving understanding of the genes, proteins, metabolic network and regulatory network of an organism. This article provides an overview of Pathway Tools capabilities. The software performs multiple computational inferences including prediction of metabolic pathways, prediction of metabolic pathway hole fillers and prediction of operons. It enables interactive editing of PGDBs by DB curators. It supports web publishing of PGDBs, and provides a large number of query and visualization tools. The software also supports comparative analyses of PGDBs, and provides several systems biology analyses of PGDBs including reachability analysis of metabolic networks, and interactive tracing of metabolites through a metabolic network. More than 800 PGDBs have been created using Pathway Tools by scientists around the world, many of which are curated DBs for important model organisms. Those PGDBs can be exchanged using a peer-to-peer DB sharing system called the PGDB Registry.

The MetaCyc Database of metabolic pathways and enzymes and the BioCyc collection of Pathway/Genome Databases.

MetaCyc (MetaCyc.org) is a universal database of metabolic pathways and enzymes from all domains of life. The pathways in MetaCyc are curated from the primary scientific literature, and are experimentally determined small-molecule metabolic pathways. Each reaction in a MetaCyc pathway is annotated with one or more well-characterized enzymes. Because MetaCyc contains only experimentally elucidated knowledge, it provides a uniquely high-quality resource for metabolic pathways and enzymes. BioCyc (BioCyc.org) is a collection of more than 350 organism-specific Pathway/Genome Databases (PGDBs). Each BioCyc PGDB contains the predicted metabolic network of one organism, including metabolic pathways, enzymes, metabolites and reactions predicted by the Pathway Tools software using MetaCyc as a reference database. BioCyc PGDBs also contain predicted operons and predicted pathway hole fillers-predictions of which enzymes may catalyze pathway reactions that have not been assigned to an enzyme. The BioCyc website offers many tools for computational analysis of PGDBs, including comparative analysis and analysis of omics data in a pathway context. The BioCyc PGDBs generated by SRI are offered for adoption by any interested party for the ongoing integration of metabolic and genome-related information about an organism.

MetaCyc: a multiorganism database of metabolic pathways and enzymes.

MetaCyc is a database of metabolic pathways and enzymes located at http://MetaCyc.org/. Its goal is to serve as a metabolic encyclopedia, containing a collection of non-redundant pathways central to small molecule metabolism, which have been reported in the experimental literature. Most of the pathways in MetaCyc occur in microorganisms and plants, although animal pathways are also represented. MetaCyc contains metabolic pathways, enzymatic reactions, enzymes, chemical compounds, genes and review-level comments. Enzyme information includes substrate specificity, kinetic properties, activators, inhibitors, cofactor requirements and links to sequence and structure databases. Data are curated from the primary literature by curators with expertise in biochemistry and molecular biology. MetaCyc serves as a readily accessible comprehensive resource on microbial and plant pathways for genome analysis, basic research, education, metabolic engineering and systems biology. Querying, visualization and curation of the database is supported by SRI's Pathway Tools software. The PathoLogic component of Pathway Tools is used in conjunction with MetaCyc to predict the metabolic network of an organism from its annotated genome. SRI and the European Bioinformatics Institute employed this tool to create pathway/genome databases (PGDBs) for 165 organisms, available at the BioCyc.org website. These PGDBs also include predicted operons and pathway hole fillers.

Expansion of the BioCyc collection of pathway/genome databases to 160 genomes.

The BioCyc database collection is a set of 160 pathway/genome databases (PGDBs) for most eukaryotic and prokaryotic species whose genomes have been completely sequenced to date. Each PGDB in the BioCyc collection describes the genome and predicted metabolic network of a single organism, inferred from the MetaCyc database, which is a reference source on metabolic pathways from multiple organisms. In addition, each bacterial PGDB includes predicted operons for the corresponding species. The BioCyc collection provides a unique resource for computational systems biology, namely global and comparative analyses of genomes and metabolic networks, and a supplement to the BioCyc resource of curated PGDBs. The Omics viewer available through the BioCyc website allows scientists to visualize combinations of gene expression, proteomics and metabolomics data on the metabolic maps of these organisms. This paper discusses the computational methodology by which the BioCyc collection has been expanded, and presents an aggregate analysis of the collection that includes the range of number of pathways present in these organisms, and the most frequently observed pathways. We seek scientists to adopt and curate individual PGDBs within the BioCyc collection. Only by harnessing the expertise of many scientists we can hope to produce biological databases, which accurately reflect the depth and breadth of knowledge that the biomedical research community is producing.