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An important emerging need in Model Organism Databases (MODs) and other bioinformatics databases (DBs) is that of capturing the scientific evidence that supports the information within a DB. This need has become particularly acute as more DB content consists of computationally predicted information, such as predicted gene functions, operons, metabolic pathways, and protein properties. This paper presents an ontology for encoding the type of support and the degree of support for DB assertions, and for encoding the literature source in which that support is reported. The ontology includes a hierarchy of 35 evidence codes for modeling different types of wet-lab and computational evidence for the existence of operons and metabolic pathways, and for gene functions. We also describe an implementation of the ontology within the Pathway Tools software environment, which is used to query and update Pathway/Genome DBs such as EcoCyc, MetaCyc, and HumanCyc.
Karp et al. (2003) studied this question.