Tools for Ontology Annotation: dcGO

点击翻译按钮获取中文摘要

The massive amount of biological data, especially sequenced genomes and their end-product protein sequences, poses a prohibitive challenge for humans to manually cross-reference in literature. The solution is to use ontologies - controlled vocabularies - so that computer systems can process and connect rational relationships that are also readable by humans. The most used ontology is Gene Ontology (GO) that intends to describe protein functions.The most used resource for GO is UniProt. It provides protein sequence and functional annotation. GO annotations for proteins have two main types of evidence: one from experimental or curated annotations, the other from IEA (Inferred Electronic Annotations). IEA comes mostly from an InterPro mapping. InterPro is an integrated database that combines protein domains (or precisely signatures) from diverse sources with different definitions. In InterPro, annotations for domains are hand-curated via homology. Recently, we have pioneered a methodology in pursuit of a fully-automated tool: domain-centric Gene Ontology (dcGO). dcGO is the only freely available fully-automated general methodology for domain-based GO annotation. Thanks to its automated nature, dcGO is much more extensive than the InterPro hand curation. By comparison, we have shown that the quality of dcGO is at least as good as InterPro in terms of function predictions of proteins in UniProt. Therefore, extending dcGO to InterPro will have a considerable downstream impact on the UniProt IEA coverage and quality which is what scientists from around the world are routinely using as their primary source of annotation. In addition to GO, we will also provide domain annotations using other biomedical ontologies such as those describing diseases and phenotypes. For these kinds of annotations, currently only the dcGO approach can be extended in this way in a straightforward manner. In CAFA, a community-based critical assessment of protein function prediction, dcGO has been demonstrated for use in automated function annotation. In the next CAFA, we will prove that dcGO is also the suitable baseline for other ontologies and thus for inclusion in InterPro and UniProt. To meet the user requests for analysing sequences as a whole, we will also provide ontology enrichment analysis that will allow the users to understand which functions (and other relevant knowledge) are overrepresented in sequences submitted. This user-driven tool will be implemented in a computationally efficient way; the required will be on the order of seconds or minutes, rather than hours or days. In summary, the proposed research will be undertaken with a tight link to InterProt, UniProt, CAFA and end-users, and these collaborative connections will help translate our domain-centric solution into the industry standard for annotating and analyzing genome sequences.