title: A survey of metabolic databases emphasizing the MetaCyc family.
abstract: 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.
authors.affiliation: Bioinformatics Research Group, SRI International, 333 Ravenswood Ave, Menlo Park, CA, 94025, USA. pkarp@ai.sri.com
authors.forename: Peter D
authors.initials: PD
authors.lastname: Karp
authors.forename: Ron
authors.initials: R
authors.lastname: Caspi
mesh_terms: D019295:Computational Biology / Q000145:classification / Q000592:standards; D016208:Databases, Factual / Q000145:classification / Q000592:standards; D030541:Databases, Genetic; D004798:Enzymes / Q000378:metabolism; D016247:Information Storage and Retrieval / Q000379:methods; D020407:Internet; D053858:Metabolic Networks and Pathways; D012984:Software; D014584:User-Computer Interface
chemical_list: D004798:Enzymes