Database Commons

a catalog of worldwide biological databases

EcoCyc (EcoCyc.org) is a freely accessible, comprehensive database that collects and summarizes experimental data for Escherichia coli K-12, the best-studied bacterial model organism. New experimental discoveries about gene products, their function and regulation, new metabolic pathways, enzymes and cofactors are regularly added to EcoCyc. New SmartTable tools allow users to browse collections of related EcoCyc content. SmartTables can also serve as repositories for user- or curator-generated lists. EcoCyc now supports running and modifying E. coli metabolic models directly on the EcoCyc website. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

EcoCyc is a bioinformatics database available at EcoCyc.org that describes the genome and the biochemical machinery of Escherichia coli K-12 MG1655. The long-term goal of the project is to describe the complete molecular catalog of the E. coli cell, as well as the functions of each of its molecular parts, to facilitate a system-level understanding of E. coli. EcoCyc is an electronic reference source for E. coli biologists, and for biologists who work with related microorganisms. The database includes information pages on each E. coli gene, metabolite, reaction, operon, and metabolic pathway. The database also includes information on E. coli gene essentiality, and on nutrient conditions that do or do not support the growth of E. coli. The web site and downloadable software contain tools for analysis of high-throughput datasets. In addition, a steady-state metabolic flux model is generated from each new version of EcoCyc. The model can predict metabolic flux rates, nutrient uptake rates, and growth rates for different gene knockouts and nutrient conditions. This chapter provides a detailed description of the data content of EcoCyc, and of the procedures by which this content is generated.

Manual extraction of information from the biomedical literature-or biocuration-is the central methodology used to construct many biological databases. For example, the UniProt protein database, the EcoCyc Escherichia coli database and the Candida Genome Database (CGD) are all based on biocuration. Biological databases are used extensively by life science researchers, as online encyclopedias, as aids in the interpretation of new experimental data and as golden standards for the development of new bioinformatics algorithms. Although manual curation has been assumed to be highly accurate, we are aware of only one previous study of biocuration accuracy. We assessed the accuracy of EcoCyc and CGD by manually selecting curated assertions within randomly chosen EcoCyc and CGD gene pages and by then validating that the data found in the referenced publications supported those assertions. A database assertion is considered to be in error if that assertion could not be found in the publication cited for that assertion. We identified 10 errors in the 633 facts that we validated across the two databases, for an overall error rate of 1.58%, and individual error rates of 1.82% for CGD and 1.40% for EcoCyc. These data suggest that manual curation of the experimental literature by Ph.D-level scientists is highly accurate. Database URL: http://ecocyc.org/, http://www.candidagenome.org//

EcoCyc (http://EcoCyc.org) is a model organism database built on the genome sequence of Escherichia coli K-12 MG1655. Expert manual curation of the functions of individual E. coli gene products in EcoCyc has been based on information found in the experimental literature for E. coli K-12-derived strains. Updates to EcoCyc content continue to improve the comprehensive picture of E. coli biology. The utility of EcoCyc is enhanced by new tools available on the EcoCyc web site, and the development of EcoCyc as a teaching tool is increasing the impact of the knowledge collected in EcoCyc.

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.

EcoCyc (http://EcoCyc.org) provides a comprehensive encyclopedia of Escherichia coli biology. EcoCyc integrates information about the genome, genes and gene products; the metabolic network; and the regulatory network of E. coli. Recent EcoCyc developments include a new initiative to represent and curate all types of E. coli regulatory processes such as attenuation and regulation by small RNAs. EcoCyc has started to curate Gene Ontology (GO) terms for E. coli and has made a dataset of E. coli GO terms available through the GO Web site. The curation and visualization of electron transfer processes has been significantly improved. Other software and Web site enhancements include the addition of tracks to the EcoCyc genome browser, in particular a type of track designed for the display of ChIP-chip datasets, and the development of a comparative genome browser. A new Genome Omics Viewer enables users to paint omics datasets onto the full E. coli genome for analysis. A new advanced query page guides users in interactively constructing complex database queries against EcoCyc. A Macintosh version of EcoCyc is now available. A series of Webinars is available to instruct users in the use of EcoCyc.

The EcoCyc database (http://EcoCyc.org/) is a comprehensive source of information on the biology of the prototypical model organism Escherichia coli K12. The mission for EcoCyc is to contain both computable descriptions of, and detailed comments describing, all genes, proteins, pathways and molecular interactions in E.coli. Through ongoing manual curation, extensive information such as summary comments, regulatory information, literature citations and evidence types has been extracted from 8862 publications and added to Version 8.5 of the EcoCyc database. The EcoCyc database can be accessed through a World Wide Web interface, while the downloadable Pathway Tools software and data files enable computational exploration of the data and provide enhanced querying capabilities that web interfaces cannot support. For example, EcoCyc contains carefully curated information that can be used as training sets for bioinformatics prediction of entities such as promoters, operons, genetic networks, transcription factor binding sites, metabolic pathways, functionally related genes, protein complexes and protein-ligand interactions.

EcoCyc is an organism-specific pathway/genome database that describes the metabolic and signal-transduction pathways of Escherichia coli, its enzymes, its transport proteins and its mechanisms of transcriptional control of gene expression. EcoCyc is queried using the Pathway Tools graphical user interface, which provides a wide variety of query operations and visualization tools. EcoCyc is available at http://ecocyc.org/.

MOTIVATION: We seek to determine the accuracy of computational methods for predicting metabolic pathways in sequenced genomes, and to understand the contributions of both the prediction algorithms, and the reference pathway databases used by those algorithms, to the prediction accuracy.
RESULTS: The comparisons we performed were as follows. (1) We compared two predictions of the pathway complements of Helicobacter pylori that were computed by an early version of our pathway-prediction algorithm: prediction A used the EcoCyc E. coli pathway DB as the reference database (DB) for prediction, and prediction B used the MetaCyc pathway DB (a superset of EcoCyc) as the reference pathway DB. The MetaCyc-based prediction contained 75% more pathway predictions, but we believe a significant number of those predictions were false positives. (2) We compared two predictions of the pathway complement of H. pylori that used MetaCyc as the reference pathway DB, but that used different algorithms: the original PathoLogic algorithm, and an enhanced version of the algorithm designed to eliminate false-positive pathway predictions. The improved algorithm predicted 30\% fewer metabolic pathways than the original algorithm; all of the eliminated pathways are believed to be false-positive predictions. (3) We compared the 98 pathways predicted by the enhanced algorithm with the results of a manual analysis of the pathways of H. pylori. Results: 40 of the computationally predicted pathways were consistent with the manual analysis, 13 pathways are considered false-positive predictions, and four pathways had partially overlapping topologies. Twenty-six predicted pathways were not mentioned in the manual analysis; we believe these are correct predictions by PathoLogic that were not found by the manual analysis. Five pathways from the manual analysis were not found computationally. Agreement between the computational and manual predictions was good overall, with the computational analysis inferring many pathways that the manual analysis did not identify. Ultimately the manual analysis is also partially speculative, and therefore is not an absolute measure of correctness. The algorithm is designed to err on the side of more false positives to bring more potential pathways to the user's attention. The resulting H. pylori pathway DB is freely available at http://ecocyc.org:1555/HPY/organism-summary?object=HPY.
AVAILABILITY: The Pathway Tools software is freely available to academic users, and is available to commercial users for a fee. Contact pkarp@ai.sri.com for information on obtaining the software.

A pathway database (DB) is a DB that describes biochemical pathways, reactions, and enzymes. The EcoCyc pathway DB (see http://ecocyc.org) describes the metabolic, transport, and genetic-regulatory networks of Escherichia coli. EcoCyc is an example of a computational symbolic theory, which is a DB that structures a scientific theory within a formal ontology so that it is available for computational analysis. It is argued that by encoding scientific theories in symbolic form, we open new realms of analysis and understanding for theories that would otherwise be too large and complex for scientists to reason with effectively.

EcoCyc is an organism-specific Pathway/Genome Database that describes the metabolic and signal-transduction pathways of Escherichia coli, its enzymes, and-a new addition-its transport proteins. MetaCyc is a new metabolic-pathway database that describes pathways and enzymes of many different organisms, with a microbial focus. Both databases are queried using the Pathway Tools graphical user interface, which provides a wide variety of query operations and visualization tools. EcoCyc and MetaCyc are available at http://ecocyc.PangeaSystems.com/ecocyc/

The EcoCyc database describes the genome and gene products of Escherichia coli, its metabolic and signal-transduction pathways, and its tRNAs. The database describes 4391 genes of E.coli, 695 enzymes encoded by a subset of these genes, 904 metabolic reactions that occur in E.coli, and the organization of these reactions into 129 metabolic pathways. The EcoCyc graphical user interface allows scientists to query and explore the EcoCyc database using visualization tools such as genomic-map browsers and automatic layouts of metabolic pathways. EcoCyc has many references to the primary literature, and is a (qualitative) computational model of E. coli metabolism. EcoCyc is available at URL http://ecocyc. PangeaSystems.com/ecocyc/

The encyclopedia of Escherichia coli genes and metabolism (EcoCyc) is a database that combines information about the genome and the intermediary metabolism of E.coli. The database describes 3030 genes of E.coli , 695 enzymes encoded by a subset of these genes, 595 metabolic reactions that occur in E.coli, and the organization of these reactions into 123 metabolic pathways. The EcoCyc graphical user interface allows scientists to query and explore the EcoCyc database using visualization tools such as genomic-map browsers and automatic layouts of metabolic pathways. EcoCyc can be thought of as an electronic review article because of its copious references to the primary literature, and as a (qualitative) computational model of E.coli metabolism. EcoCyc is available at URL http://ecocyc.PangeaSystems.com/ecocyc/

The Encyclopedia of Genes and Metabolism (EcoCyc) is a database that combines information about the genome and the intermediary metabolism of Escherichia coli. It describes 2970 genes of E.coli, 547 enzymes encoded by these genes, 702 metabolic reactions that occur in E.coli and the organization of these reactions into 107 metabolic pathways. The EcoCyc graphical user interface allows scientists to query and explore the EcoCyc database using visualization tools such as genomic-map browsers and automatic layouts of metabolic pathways. EcoCyc spans the space from sequence to function to allow scientists to investigate an unusually broad range of questions. EcoCyc can be thought of as both an electronic review article because of its copious references to the primary literature, and as an in silicio model of E.coli metabolism that can be probed and analyzed through computational means.

The encyclopedia of Escherichia coli genes and metabolism (EcoCyc) is a database that combines information about the genome and the intermediary metabolism of E.coli. It describes 2034 genes, 306 enzymes encoded by these genes, 580 metabolic reactions that occur in E.coli and the organization of these reactions into 100 metabolic pathways. The EcoCyc graphical user interface allows query and exploration of the EcoCyc database using visualization tools such as genomic map browsers and automatic layouts of metabolic pathways. EcoCyc spans the space from sequence to function to allow investigation of an unusually broad range of questions. EcoCyc can be thought of as both an electronic review article, because of its copious references to the primary literature, and as an in silico model of E.coli that can be probed and analyzed through computational means.