7588 Nucleic Acids Research, 2007, Vol. 35, No. 22 (ii) Functions are assigned to gene products, both as textual descriptions and as descriptions within the MultiFun Ontology and Gene Ontology. (iii) Gene products are assigned to macromolecular complexes in which they function. Chemically modiﬁed states of gene products are deﬁned when appropriate. (iv) A long-term literature curation eﬀort has popu- lated EcoCyc with information from 15 000 publications. Every gene product for which experi- mental literature is likely available (3332 ORFs) contains a mini-review summary of what is known about the gene product, forming another dimen- sion of annotation. Similar summaries are found in pathway objects and transcription unit objects within EcoCyc. (v) The functions of 3384 (76%) E. coli genes have been determined through wet-lab experimentation, which is signiﬁcantly higher in both relative and absolute terms than for any other model organism. EcoCyc encodes the type of evidence supporting the functions of gene products, and of other entities including operons, promoters, transcription factor binding sites and pathways. (vi) EcoCyc represents the transcriptional regulatory network of E. coli. The network describes tran- scriptional control of 718 TUs by 171 transcription factors. EcoCyc speciﬁcally represents the binding of these 171 factors to 1790 transcription factor binding sites, 1625 of which have experimental (wet lab) evidence. In addition, EcoCyc records the interactions by which 49 small-molecule ligands control the activities of the 171 transcription factors. A novel interactive visualization of the transcriptional regulatory network is available. (vii) The metabolic network of E. coli as represented in EcoCyc consists of 194 metabolic pathways con- taining 722 reactions, plus an additional 286 reactions not assigned to a pathway. Database queries making use of this structured representa- tion of E. coli metabolism identiﬁed gaps in the network, including reactions whose catalyzing enzymes have not been identiﬁed, and dead-end metabolites. These gaps guided additional curation eﬀorts that either corrected representational con- cerns, found additional evidence in the literature, or identiﬁed matching gaps in our knowledge of E. coli biology. (viii) Representation of transporters adds additional depth to the metabolic network in EcoCyc. The transport complement of E. coli consists of 214 transport proteins of known function that facilitate the transport of 180 substrates. As described above, an understanding of transporters is critical in evaluating the role of any metabolite in the overall metabolic network. A number of other E. coli databases exist that provide annotated gene/protein content. Some provide comple- mentary information while others share overlap. However, none provide the range of dimensional content and accessibility to the E. coli genome within EcoCyc. For example, EcoGene (26) focuses on corrections to the E. coli MG1655 sequence, and to gene start and stop positions. It also contains many literature citations, and a limited set of short gene summaries, most of which do not contain internal citations that provide sources for speciﬁc statements. The Coli Genetic Stock Center (see http:// cgsc.biology.yale.edu/) provides valuable information on E. coli strains and mutations. It contains some short summaries that do not contain internal citations that provide sources for speciﬁc statements. KEGG (27) describes the E. coli genome annotation and its metabolic pathways. It contains no summaries or citations, and the user cannot determine what information in KEGG is literature curated versus predicted computationally. None of these databases provide evidence codes. EchoBASE (28) describes the E. coli genome annotation, providing some summaries that lack internal citations; and it provides high-throughput datasets for E. coli. UniProt (29) contains information about the E. coli proteome, including summaries and literature citations, although many functional assignments lack speciﬁc literature support. RegulonDB (14) describes the transcriptional regulatory network of E. coli. The RefSeq E. coli entry contains genome annotation information combined from several of the preceding databases. A number of other E. coli databases exist (see http://www.uni-gies sen.de/ gx1052/IECA/ieca.html), although some have not been updated for many years. The goal of EcoCyc is to accelerate scientiﬁc discovery and education. We recently surveyed more than 500 publications that cite EcoCyc, and found that their uses of EcoCyc fell into ﬁve major classes. (i) EcoCyc is a knowledge resource on the E. coli genome and cellular networks for experimentalists who work with E. coli, with other microbes, and with higher organisms. Scientists use it as an encyclopedic reference, particularly for analyzing large-scale datasets, such as for analyzing E. coli gene- expression data. (ii) Computational biologists use EcoCyc to answer biological questions using computational methods, such as assessing which metabolic enzymes are conserved between yeast and E. coli (30), studying the topological organization of the E. coli metabolic network (31), and studying the properties of the E. coli transcrip- tional regulatory network (32). (iii) Bioinformaticists use EcoCyc as a gold-standard data source for developing and validating new prediction algorithms, such as genome context algorithms for predicting functional relationships among proteins (33,34), operon predictors (34) and algorithms for predicting regulatory networks from gene expression data (35). (iv) Metabolic engineers consult EcoCyc when altering the metabolic network of E. coli (36). (v) University courses make use of EcoCyc in subjects ranging from microbial physiology through molecular genetics to microbial biotechnology. The guiding principle of the EcoCyc project has been to store information about E. coli gene function and cellular networks within a structured ontology that makes those data readily accessible to symbolic systems biology computations (37). We have illustrated several such analyses in this article that use computational methods