Assessment of genome annotation using gene function similarity within the gene neighborhood
Se-Ran Jun, Intawat Nookaew, Loren Hauser, and Andrey Gorin
12 July 2017, BMC Bioinformatics 18:345; DOI: 10.1186/s12859-017-1761-2
Background:Functional annotation of bacterial genomes is an obligatory and crucially important step of information processing from the genome sequences into cellular mechanisms. However, there is a lack of computational methods to evaluate the quality of functional assignments. Results:We developed a genome-scale model that assigns Bayesian probability to each gene utilizing a known property of functional similarity between neighboring genes in bacteria. Conclusion:Our model clearly distinguished true annotation from random annotation with Bayesian annotation probability <0.95. Our model will provide a useful guide to quantitatively evaluate functional annotation methods and to detect gene sets with reliable annotations.
Jun, S.-R., Nookaew, I., Hauser, L., & Gorin, A. (2017). Assessment of genome annotation using gene function similarity within the gene neighborhood. BMC Bioinformatics, 18, 345. http://doi.org/10.1186/s12859-017-1761-2