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Ron Caspi - One of the best experts on this subject based on the ideXlab platform.
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the MetaCyc database of metabolic pathways and enzymes a 2019 update
Nucleic Acids Research, 2020Co-Authors: Ron Caspi, Suzanne M Paley, Anamika Kothari, Markus Krummenacker, Richard Billington, Ingrid M Keseler, Peter E Midford, Wai Kit Ong, Pallavi Subhraveti, Peter D KarpAbstract:MetaCyc (MetaCyc.org) is a comprehensive reference database of metabolic pathways and enzymes from all domains of life. It contains 2749 pathways derived from more than 60 000 publications, making it the largest curated collection of metabolic pathways. The data in MetaCyc are evidence-based and richly curated, resulting in an encyclopedic reference tool for metabolism. MetaCyc is also used as a knowledge base for generating thousands of organism-specific Pathway/Genome Databases (PGDBs), which are available in BioCyc.org and other genomic portals. This article provides an update on the developments in MetaCyc during September 2017 to August 2019, up to version 23.1. Some of the topics that received intensive curation during this period include cobamides biosynthesis, sterol metabolism, fatty acid biosynthesis, lipid metabolism, carotenoid metabolism, protein glycosylation, antibiotics and cytotoxins biosynthesis, siderophore biosynthesis, bioluminescence, vitamin K metabolism, brominated compound metabolism, plant secondary metabolism and human metabolism. Other additions include modifications to the GlycanBuilder software that enable displaying glycans using symbolic representation, improved graphics and fonts for web displays, improvements in the PathoLogic component of Pathway Tools, and the optional addition of regulatory information to pathway diagrams.
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the MetaCyc database of metabolic pathways and enzymes
Nucleic Acids Research, 2018Co-Authors: Ron Caspi, Anamika Kothari, Carol A Fulcher, Markus Krummenacker, Richard Billington, Ingrid M Keseler, Mario Latendresse, Peter E Midford, Quang Ong, Wai Kit OngAbstract:MetaCyc (https://MetaCyc.org) is a comprehensive reference database of metabolic pathways and enzymes from all domains of life. It contains more than 2570 pathways derived from >54 000 publications, making it the largest curated collection of metabolic pathways. The data in MetaCyc is strictly evidence-based and richly curated, resulting in an encyclopedic reference tool for metabolism. MetaCyc is also used as a knowledge base for generating thousands of organism-specific Pathway/Genome Databases (PGDBs), which are available in the BioCyc (https://BioCyc.org) and other PGDB collections. This article provides an update on the developments in MetaCyc during the past two years, including the expansion of data and addition of new features.
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a systematic comparison of the MetaCyc and kegg pathway databases
BMC Bioinformatics, 2013Co-Authors: Tomer Altman, Ron Caspi, Michael Travers, Anamika Kothari, Peter D KarpAbstract:The MetaCyc and KEGG projects have developed large metabolic pathway databases that are used for a variety of applications including genome analysis and metabolic engineering. We present a comparison of the compound, reaction, and pathway content of MetaCyc version 16.0 and a KEGG version downloaded on Feb-27-2012 to increase understanding of their relative sizes, their degree of overlap, and their scope. To assess their overlap, we must know the correspondences between compounds, reactions, and pathways in MetaCyc, and those in KEGG. We devoted significant effort to computational and manual matching of these entities, and we evaluated the accuracy of the correspondences. KEGG contains 179 module pathways versus 1,846 base pathways in MetaCyc; KEGG contains 237 map pathways versus 296 super pathways in MetaCyc. KEGG pathways contain 3.3 times as many reactions on average as do MetaCyc pathways, and the databases employ different conceptualizations of metabolic pathways. KEGG contains 8,692 reactions versus 10,262 for MetaCyc. 6,174 KEGG reactions are components of KEGG pathways versus 6,348 for MetaCyc. KEGG contains 16,586 compounds versus 11,991 for MetaCyc. 6,912 KEGG compounds act as substrates in KEGG reactions versus 8,891 for MetaCyc. MetaCyc contains a broader set of database attributes than does KEGG, such as relationships from a compound to enzymes that it regulates, identification of spontaneous reactions, and the expected taxonomic range of metabolic pathways. MetaCyc contains many pathways not found in KEGG, from plants, fungi, metazoa, and actinobacteria; KEGG contains pathways not found in MetaCyc, for xenobiotic degradation, glycan metabolism, and metabolism of terpenoids and polyketides. MetaCyc contains fewer unbalanced reactions, which facilitates metabolic modeling such as using flux-balance analysis. MetaCyc includes generic reactions that may be instantiated computationally. KEGG contains significantly more compounds than does MetaCyc, whereas MetaCyc contains significantly more reactions and pathways than does KEGG, in particular KEGG modules are quite incomplete. The number of reactions occurring in pathways in the two DBs are quite similar.
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A survey of metabolic databases emphasizing the MetaCyc family
Archives of Toxicology, 2011Co-Authors: Peter D Karp, Ron CaspiAbstract:Thanks to the confluence of genome sequencing and bioinformatics, the number of metabolic databases has expanded from a handful in the mid-1990s to several thousand today. These databases lie within distinct families that have common ancestry and common attributes. The main families are the MetaCyc, KEGG, Reactome, Model SEED, and BiGG families. We survey these database families, as well as important individual metabolic databases, including multiple human metabolic databases. The MetaCyc family is described in particular detail. It contains well over 1,000 databases, including highly curated databases for Escherichia coli , Saccharomyces cerevisiae , Mus musculus , and Arabidopsis thaliana . These databases are available through a number of web sites that offer a range of software tools for querying and visualizing metabolic networks. These web sites also provide multiple tools for analysis of gene expression and metabolomics data, including visualization of those datasets on metabolic network diagrams and over-representation analysis of gene sets and metabolite sets.
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creation of a genome wide metabolic pathway database for populus trichocarpa using a new approach for reconstruction and curation of metabolic pathways for plants
Plant Physiology, 2010Co-Authors: Peifen Zhang, Anuradha Pujar, Ron Caspi, Peter D Karp, Mario Latendresse, Kate Dreher, A Karthikeyan, Anjo Chi, Vanessa Kirkup, Cynthia LeeAbstract:Metabolic networks reconstructed from sequenced genomes or transcriptomes can help visualize and analyze large-scale experimental data, predict metabolic phenotypes, discover enzymes, engineer metabolic pathways, and study metabolic pathway evolution. We developed a general approach for reconstructing metabolic pathway complements of plant genomes. Two new reference databases were created and added to the core of the infrastructure: a comprehensive, all-plant reference pathway database, PlantCyc, and a reference enzyme sequence database, RESD, for annotating metabolic functions of protein sequences. PlantCyc (version 3.0) includes 714 metabolic pathways and 2,619 reactions from over 300 species. RESD (version 1.0) contains 14,187 literature-supported enzyme sequences from across all kingdoms. We used RESD, PlantCyc, and MetaCyc (an all-species reference metabolic pathway database), in conjunction with the pathway prediction software Pathway Tools, to reconstruct a metabolic pathway database, PoplarCyc, from the recently sequenced genome of Populus trichocarpa. PoplarCyc (version 1.0) contains 321 pathways with 1,807 assigned enzymes. Comparing PoplarCyc (version 1.0) with AraCyc (version 6.0, Arabidopsis [Arabidopsis thaliana]) showed comparable numbers of pathways distributed across all domains of metabolism in both databases, except for a higher number of AraCyc pathways in secondary metabolism and a 1.5-fold increase in carbohydrate metabolic enzymes in PoplarCyc. Here, we introduce these new resources and demonstrate the feasibility of using them to identify candidate enzymes for specific pathways and to analyze metabolite profiling data through concrete examples. These resources can be searched by text or BLAST, browsed, and downloaded from our project Web site (http://plantcyc.org).
Peter D Karp - One of the best experts on this subject based on the ideXlab platform.
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the MetaCyc database of metabolic pathways and enzymes a 2019 update
Nucleic Acids Research, 2020Co-Authors: Ron Caspi, Suzanne M Paley, Anamika Kothari, Markus Krummenacker, Richard Billington, Ingrid M Keseler, Peter E Midford, Wai Kit Ong, Pallavi Subhraveti, Peter D KarpAbstract:MetaCyc (MetaCyc.org) is a comprehensive reference database of metabolic pathways and enzymes from all domains of life. It contains 2749 pathways derived from more than 60 000 publications, making it the largest curated collection of metabolic pathways. The data in MetaCyc are evidence-based and richly curated, resulting in an encyclopedic reference tool for metabolism. MetaCyc is also used as a knowledge base for generating thousands of organism-specific Pathway/Genome Databases (PGDBs), which are available in BioCyc.org and other genomic portals. This article provides an update on the developments in MetaCyc during September 2017 to August 2019, up to version 23.1. Some of the topics that received intensive curation during this period include cobamides biosynthesis, sterol metabolism, fatty acid biosynthesis, lipid metabolism, carotenoid metabolism, protein glycosylation, antibiotics and cytotoxins biosynthesis, siderophore biosynthesis, bioluminescence, vitamin K metabolism, brominated compound metabolism, plant secondary metabolism and human metabolism. Other additions include modifications to the GlycanBuilder software that enable displaying glycans using symbolic representation, improved graphics and fonts for web displays, improvements in the PathoLogic component of Pathway Tools, and the optional addition of regulatory information to pathway diagrams.
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a systematic comparison of the MetaCyc and kegg pathway databases
BMC Bioinformatics, 2013Co-Authors: Tomer Altman, Ron Caspi, Michael Travers, Anamika Kothari, Peter D KarpAbstract:The MetaCyc and KEGG projects have developed large metabolic pathway databases that are used for a variety of applications including genome analysis and metabolic engineering. We present a comparison of the compound, reaction, and pathway content of MetaCyc version 16.0 and a KEGG version downloaded on Feb-27-2012 to increase understanding of their relative sizes, their degree of overlap, and their scope. To assess their overlap, we must know the correspondences between compounds, reactions, and pathways in MetaCyc, and those in KEGG. We devoted significant effort to computational and manual matching of these entities, and we evaluated the accuracy of the correspondences. KEGG contains 179 module pathways versus 1,846 base pathways in MetaCyc; KEGG contains 237 map pathways versus 296 super pathways in MetaCyc. KEGG pathways contain 3.3 times as many reactions on average as do MetaCyc pathways, and the databases employ different conceptualizations of metabolic pathways. KEGG contains 8,692 reactions versus 10,262 for MetaCyc. 6,174 KEGG reactions are components of KEGG pathways versus 6,348 for MetaCyc. KEGG contains 16,586 compounds versus 11,991 for MetaCyc. 6,912 KEGG compounds act as substrates in KEGG reactions versus 8,891 for MetaCyc. MetaCyc contains a broader set of database attributes than does KEGG, such as relationships from a compound to enzymes that it regulates, identification of spontaneous reactions, and the expected taxonomic range of metabolic pathways. MetaCyc contains many pathways not found in KEGG, from plants, fungi, metazoa, and actinobacteria; KEGG contains pathways not found in MetaCyc, for xenobiotic degradation, glycan metabolism, and metabolism of terpenoids and polyketides. MetaCyc contains fewer unbalanced reactions, which facilitates metabolic modeling such as using flux-balance analysis. MetaCyc includes generic reactions that may be instantiated computationally. KEGG contains significantly more compounds than does MetaCyc, whereas MetaCyc contains significantly more reactions and pathways than does KEGG, in particular KEGG modules are quite incomplete. The number of reactions occurring in pathways in the two DBs are quite similar.
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data mining in the MetaCyc family of pathway databases
Methods of Molecular Biology, 2013Co-Authors: Peter D Karp, Suzanne M Paley, Tomer AltmanAbstract:Pathway databases collect the bioreactions and molecular interactions that define the processes of life. The MetaCyc family of pathway databases consists of thousands of databases that were derived through computational inference of metabolic pathways from the MetaCyc Pathway/Genome Database (PGDB). In some cases these DBs underwent subsequent manual curation. Curated pathway DBs are now available for most of the major model organisms. Databases in the MetaCyc family are managed using the Pathway Tools software. This chapter presents methods for performing data mining on the MetaCyc family of pathway DBs. We discuss the major data access mechanisms for the family, which include data files in multiple formats; application programming interfaces (APIs) for the Lisp, Java, and Perl languages; and web services. We present an overview of the Pathway Tools schema, an understanding of which is needed to query the DBs. The chapter also presents several interactive data mining tools within Pathway Tools for performing omics data analysis.
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A survey of metabolic databases emphasizing the MetaCyc family
Archives of Toxicology, 2011Co-Authors: Peter D Karp, Ron CaspiAbstract:Thanks to the confluence of genome sequencing and bioinformatics, the number of metabolic databases has expanded from a handful in the mid-1990s to several thousand today. These databases lie within distinct families that have common ancestry and common attributes. The main families are the MetaCyc, KEGG, Reactome, Model SEED, and BiGG families. We survey these database families, as well as important individual metabolic databases, including multiple human metabolic databases. The MetaCyc family is described in particular detail. It contains well over 1,000 databases, including highly curated databases for Escherichia coli , Saccharomyces cerevisiae , Mus musculus , and Arabidopsis thaliana . These databases are available through a number of web sites that offer a range of software tools for querying and visualizing metabolic networks. These web sites also provide multiple tools for analysis of gene expression and metabolomics data, including visualization of those datasets on metabolic network diagrams and over-representation analysis of gene sets and metabolite sets.
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creation of a genome wide metabolic pathway database for populus trichocarpa using a new approach for reconstruction and curation of metabolic pathways for plants
Plant Physiology, 2010Co-Authors: Peifen Zhang, Anuradha Pujar, Ron Caspi, Peter D Karp, Mario Latendresse, Kate Dreher, A Karthikeyan, Anjo Chi, Vanessa Kirkup, Cynthia LeeAbstract:Metabolic networks reconstructed from sequenced genomes or transcriptomes can help visualize and analyze large-scale experimental data, predict metabolic phenotypes, discover enzymes, engineer metabolic pathways, and study metabolic pathway evolution. We developed a general approach for reconstructing metabolic pathway complements of plant genomes. Two new reference databases were created and added to the core of the infrastructure: a comprehensive, all-plant reference pathway database, PlantCyc, and a reference enzyme sequence database, RESD, for annotating metabolic functions of protein sequences. PlantCyc (version 3.0) includes 714 metabolic pathways and 2,619 reactions from over 300 species. RESD (version 1.0) contains 14,187 literature-supported enzyme sequences from across all kingdoms. We used RESD, PlantCyc, and MetaCyc (an all-species reference metabolic pathway database), in conjunction with the pathway prediction software Pathway Tools, to reconstruct a metabolic pathway database, PoplarCyc, from the recently sequenced genome of Populus trichocarpa. PoplarCyc (version 1.0) contains 321 pathways with 1,807 assigned enzymes. Comparing PoplarCyc (version 1.0) with AraCyc (version 6.0, Arabidopsis [Arabidopsis thaliana]) showed comparable numbers of pathways distributed across all domains of metabolism in both databases, except for a higher number of AraCyc pathways in secondary metabolism and a 1.5-fold increase in carbohydrate metabolic enzymes in PoplarCyc. Here, we introduce these new resources and demonstrate the feasibility of using them to identify candidate enzymes for specific pathways and to analyze metabolite profiling data through concrete examples. These resources can be searched by text or BLAST, browsed, and downloaded from our project Web site (http://plantcyc.org).
Michael Y. Galperin - One of the best experts on this subject based on the ideXlab platform.
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the 2010 nucleic acids research database issue and online database collection a community of data resources
Nucleic Acids Research, 2010Co-Authors: Guy R Cochrane, Michael Y. GalperinAbstract:The current issue of Nucleic Acids Research includes descriptions of 58 new and 73 updated data resources. The accompanying online Database Collection, available at http://www.oxfordjournals.org/nar/database/a/, now lists 1230 carefully selected databases covering various aspects of molecular and cell biology. While most data resource descriptions remain very brief, the issue includes several longer papers that highlight recent significant developments in such databases as Pfam, MetaCyc, UniProt, ELM and PDBe. The databases described in the Database Issue and Database Collection, however, are far more than a distinct set of resources; they form a network of connected data, concepts and shared technology. The full content of the Database Issue is available online at the Nucleic Acids Research web site (http://nar.oxfordjournals.org/).
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the 2010 nucleic acids research database issue and online database collection a community of data resources
Nucleic Acids Research, 2010Co-Authors: Guy R Cochrane, Michael Y. GalperinAbstract:The current issue of Nucleic Acids Research includes descriptions of 58 new and 73 updated data resources. The accompanying online Database Collection, available at http://www.oxfordjournals.org/nar/database/a/, now lists 1230 carefully selected databases covering various aspects of molecular and cell biology. While most data resource descriptions remain very brief, the issue includes several longer papers that highlight recent significant developments in such databases as Pfam, MetaCyc, UniProt, ELM and PDBe. The databases described in the Database Issue and Database Collection, however, are far more than a distinct set of resources; they form a network of connected data, concepts and shared technology. The full content of the Database Issue is available online at the Nucleic Acids Research web site (http://nar.oxfordjournals.org/).
Seung Y Rhee - One of the best experts on this subject based on the ideXlab platform.
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MetaCyc and aracyc metabolic pathway databases for plant research
Plant Physiology, 2005Co-Authors: Peifen Zhang, Lukas A Mueller, Peter D Karp, Suzanne M Paley, Hartmut Foerster, Christophe Tissier, Seung Y RheeAbstract:MetaCyc (http://MetaCyc.org) contains experimentally determined biochemical pathways to be used as a reference database for metabolism. In conjunction with the Pathway Tools software, MetaCyc can be used to computationally predict the metabolic pathway complement of an annotated genome. To increase the breadth of pathways and enzymes, more than 60 plant-specific pathways have been added or updated in MetaCyc recently. In contrast to MetaCyc, which contains metabolic data for a wide range of organisms, AraCyc is a species-specific database containing only enzymes and pathways found in the model plant Arabidopsis (Arabidopsis thaliana). AraCyc (http://arabidopsis.org/tools/aracyc/) was the first computationally predicted plant metabolism database derived from MetaCyc. Since its initial computational build, AraCyc has been under continued curation to enhance data quality and to increase breadth of pathway coverage. Twenty-eight pathways have been manually curated from the literature recently. Pathway predictions in AraCyc have also been recently updated with the latest functional annotations of Arabidopsis genes that use controlled vocabulary and literature evidence. AraCyc currently features 1,418 unique genes mapped onto 204 pathways with 1,156 literature citations. The Omics Viewer, a user data visualization and analysis tool, allows a list of genes, enzymes, or metabolites with experimental values to be painted on a diagram of the full pathway map of AraCyc. Other recent enhancements to both MetaCyc and AraCyc include implementation of an evidence ontology, which has been used to provide information on data quality, expansion of the secondary metabolism node of the pathway ontology to accommodate curation of secondary metabolic pathways, and enhancement of the cellular component ontology for storing and displaying enzyme and pathway locations within subcellular compartments.
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MetaCyc a multiorganism database of metabolic pathways and enzymes
Nucleic Acids Research, 2004Co-Authors: Ron Caspi, Suzanne M Paley, Hartmut Foerster, Carol A Fulcher, Rebecca Hopkinson, John L Ingraham, Pallavi Kaipa, Markus Krummenacker, John Pick, Seung Y RheeAbstract: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.
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MetaCyc a multiorganism database of metabolic pathways and enzymes
Nucleic Acids Research, 2004Co-Authors: Ron Caspi, Suzanne M Paley, Hartmut Foerster, Carol A Fulcher, Rebecca Hopkinson, John L Ingraham, Pallavi Kaipa, Markus Krummenacker, John Pick, Seung Y RheeAbstract:The MetaCyc database (see URL http://MetaCyc.org) is a collection of metabolic pathways and enzymes from a wide variety of organisms, primarily microorganisms and plants. The goal of MetaCyc is to contain a representative sample of each experimentally elucidated pathway, and thereby to catalog the universe of metabolism. MetaCyc also describes reactions, chemical compounds and genes. Many of the pathways and enzymes in MetaCyc contain extensive information, including comments and literature citations. SRI’s Pathway Tools software supports querying, visualization and curation of MetaCyc. With its wide breadth and depth of metabolic information, MetaCyc is a valuable resource for a variety of applications. MetaCyc is the reference database of pathways and enzymes that is used in conjunction with SRI’s metabolic pathway prediction program to create Pathway/Genome Databases that can be augmented with curation from the scientific literature and published on the world wide web. MetaCyc also serves as a readily accessible comprehensive resource on microbial and plant pathways for genome analysis, basic research, education, metabolic engineering and systems biology. In the past 2 years the data content and the Pathway Tools software used to query, visualize and edit MetaCyc have been expanded significantly. These enhancements are described in this paper.
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aracyc a biochemical pathway database for arabidopsis
Plant Physiology, 2003Co-Authors: Lukas A Mueller, Peifen Zhang, Seung Y RheeAbstract:AraCyc is a database containing biochemical pathways of Arabidopsis, developed at The Arabidopsis Information Resource (http://www.arabidopsis.org). The aim of AraCyc is to represent Arabidopsis metabolism as completely as possible with a user-friendly Web-based interface. It presently features more than 170 pathways that include information on compounds, intermediates, cofactors, reactions, genes, proteins, and protein subcellular locations. The database uses Pathway Tools software, which allows the users to visualize a bird9s eye view of all pathways in the database down to the individual chemical structures of the compounds. The database was built using Pathway Tools9 Pathologic module with MetaCyc, a collection of pathways from more than 150 species, as a reference database. This initial build was manually refined and annotated. More than 20 plant-specific pathways, including carotenoid, brassinosteroid, and gibberellin biosyntheses have been added from the literature. A list of more than 40 plant pathways will be added in the coming months. The quality of the initial, automatic build of the database was compared with the manually improved version, and with EcoCyc, an Escherichia coli database using the same software system that has been manually annotated for many years. In addition, a Perl interface, PerlCyc, was developed that allows programmers to access Pathway Tools databases from the popular Perl language. AraCyc is available at the tools section of The Arabidopsis Information Resource Web site (http://www.arabidopsis.org/tools/aracyc).
Guy R Cochrane - One of the best experts on this subject based on the ideXlab platform.
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the 2010 nucleic acids research database issue and online database collection a community of data resources
Nucleic Acids Research, 2010Co-Authors: Guy R Cochrane, Michael Y. GalperinAbstract:The current issue of Nucleic Acids Research includes descriptions of 58 new and 73 updated data resources. The accompanying online Database Collection, available at http://www.oxfordjournals.org/nar/database/a/, now lists 1230 carefully selected databases covering various aspects of molecular and cell biology. While most data resource descriptions remain very brief, the issue includes several longer papers that highlight recent significant developments in such databases as Pfam, MetaCyc, UniProt, ELM and PDBe. The databases described in the Database Issue and Database Collection, however, are far more than a distinct set of resources; they form a network of connected data, concepts and shared technology. The full content of the Database Issue is available online at the Nucleic Acids Research web site (http://nar.oxfordjournals.org/).
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the 2010 nucleic acids research database issue and online database collection a community of data resources
Nucleic Acids Research, 2010Co-Authors: Guy R Cochrane, Michael Y. GalperinAbstract:The current issue of Nucleic Acids Research includes descriptions of 58 new and 73 updated data resources. The accompanying online Database Collection, available at http://www.oxfordjournals.org/nar/database/a/, now lists 1230 carefully selected databases covering various aspects of molecular and cell biology. While most data resource descriptions remain very brief, the issue includes several longer papers that highlight recent significant developments in such databases as Pfam, MetaCyc, UniProt, ELM and PDBe. The databases described in the Database Issue and Database Collection, however, are far more than a distinct set of resources; they form a network of connected data, concepts and shared technology. The full content of the Database Issue is available online at the Nucleic Acids Research web site (http://nar.oxfordjournals.org/).