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

By Ron Caspi, Tomer Altman, Kate Dreher, Carol A. Fulcher, Pallavi Subhraveti, I. Keseler, Anamika Kothari, Markus Krummenacker, Mario Latendresse, Lukas A. Mueller and 8 more. 2009

2,136 citations recorded by the source corpus.

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.

Subfields: Computational Theory and Mathematics, Molecular Biology, Evaluation & Benchmarks

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Citations in the corpus

Snorkel: Rapid Training Data Creation with Weak Supervision (2017, methodology): “We used the chemical reactions described in the Metacyc database [8] for distant supervision.”
InterPro in 2017—beyond protein family and domain annotations (2016, background): “InterPro entries are also automatically annotated with cross-references to a range of relevant databases, including the pathway databases ENZYME (18), MetaCyc (19), UniPathway (20) and KEGG (21), and various 3D structure databases (22,23).”
BRENDA in 2013: integrated reactions, kinetic data, enzyme function data, improved disease classification: new options and contents in BRENDA (2012, methodology): “In this respect it is different from other enzyme databases which are specialized either on the nomenclature [ExplorEnz, ENZYME (20), IntEnz (21)], on the metabolic pathways (e.g. KEGG, MetaCyc) or on specific classes of enzymes [e.g. Merops (22), MODOMICS (23), CAZy (24), Kinomer (25)].”
EcoCyc: fusing model organism databases with systems biology (2012, background): “EcoCyc is part of the BioCyc collection of organism-speciﬁc pathway/genome databases at http://BioCyc.org (2).”
PATRIC: the Comprehensive Bacterial Bioinformatics Resource with a Focus on Human Pathogenic Species (2011, methodology): “Finally, our cyberinfrastructure technology enables PATRIC to support additional annotations that speciﬁc communities implement for their focal organisms, such as curated MetaCyc data (12).”
The MetaCyc database of metabolic pathways and enzymes and the BioCyc collection of Pathway/Genome Databases (2013, background): “Since the last Nucleic Acids Research publication (2 years ago) (1), we added 384 new base pathways (pathways comprised of reactions only, where no portion of the pathway is designated as a subpathway) and 33 superpathways (pathways composed of at least one base pathway plus additional reactions or ”
IMG: the integrated microbial genomes database and comparative analysis system (2011, methodology): “The MetaCyc collection of pathways (16) is also available in IMG, whereby the association of MetaCyc pathways with IMG genomes is based on correlating enzyme EC numbers in MetaCyc reactions with EC numbers associated with IMG genes via KO terms.”
Predicting Network Activity from High Throughput Metabolomics (2013, methodology): “(TIF) Figure S6 Validation of mummichog on the human urine data set (Roux et al 2012), using metabolic model from BioCyc database.”
FireDB: a compendium of biological and pharmacologically relevant ligands (2013, methodology): “We selected the KEGG COMPOUND database (25) and MetaCyc (26) in order to cross-reference possible new COGNATE compounds.”
Plant Defense against Insect Herbivores (2013, background): “(a) nicotine, a true alkaloid derived from aspartate and ornithine; (b) DIMBOA, a benzoxazinoide derived from indole-3-glycerol phosphate; (c) Dhurrin, a cyanogenic glucoside derived from tyrosine, (d) Sinalbin, a glucosinolate derived from tyrosine; (e) Canavanine, a nonprotein amino acid derived f”
The InterPro protein families database: the classification resource after 15 years (2014, background): “Semi-automatic procedures create and maintain links to a range of other databases, including the protein interaction database IntAct (14), the ENZYME (15), MetaCyc (16), UniPathway (17) D ow naded rom http/academ ic.”
MicroScope—an integrated microbial resource for the curation and comparative analysis of genomic and metabolic data (2012, methodology): “This generated set of functional annotations involving enzymatic activities is then the starting point for metabolic pathway reconstructions using the PathoLogic software (10) and the MetaCyc pathway reference database (11).”
SMPDB: The Small Molecule Pathway Database (2009, background): “The HumanCyc database contains 349 pathways, including 29 superpathways (supersets of many of the other 320 pathways in the database).”
metaX: a flexible and comprehensive software for processing metabolomics data (2017, methodology): “Currently, metaX provides a function for metabolite identification based on the Human Metabolome Data-base (HMDB) [31], KEGG [32, 33], MassBank [34], Pub-Chem [35], LIPID MAPS [36], MetaCyc [37] and PlantCyc (www.plantcyc.org).”
SMPDB 2.0: Big Improvements to the Small Molecule Pathway Database (2013, background): “0, all SMPDB curators were also required to consult a variety of sources including biochemistry textbooks, OMIM (13), Wikipedia, KEGG (1), MetaCyc (3), Reactome (4), UniProt (11), the HMDB (10), DrugBank (9) and PharmGKB (6).”