GOPET: A tool for automated predictions of Gene Ontology terms. BACKGROUND: Vast progress in sequencing projects has called for annotation on a large scale. A Number of methods have been developed to address this challenging task. These methods, however, either apply to specific subsets, or their predictions are not formalised, or they do not provide precise confidence values for their predictions. DESCRIPTION: We recently established a learning system for automated annotation, trained with a broad variety of different organisms to predict the standardised annotation terms from Gene Ontology (GO). Now, this method has been made available to the public via our web-service GOPET (Gene Ontology term Prediction and Evaluation Tool). It supplies annotation for sequences of any organism. For each predicted term an appropriate confidence value is provided. The basic method had been developed for predicting molecular function GO-terms. It is now expanded to predict biological process terms. This web service is available via http://genius.embnet.dkfz-heidelberg.de/menu/biounit/open-husar CONCLUSION: Our web service gives experimental researchers as well as the bioinformatics community a valuable sequence annotation device. Additionally, GOPET also provides less significant annotation data which may serve as an extended discovery platform for the user.
References in zbMATH (referenced in 2 articles )
Showing results 1 to 2 of 2.
- Ricardo Vencio, Ilya Shmulevich: ProbCD: enrichment analysis accounting for categorization uncertainty (2007) arXiv
- Vêncio, Ricardo Zn; Shmulevich, Ilya: Probcd: Enrichment analysis accounting for categorization uncertainty (2007) ioport