title: Automatic policing of biochemical annotations using genomic correlations.
abstract: With the increasing role of computational tools in the analysis of sequenced genomes, there is an urgent need to maintain high accuracy of functional annotations. Misannotations can be easily generated and propagated through databases by functional transfer based on sequence homology. We developed and optimized an automatic policing method to detect biochemical misannotations using context genomic correlations. The method works by finding genes with unusually weak genomic correlations in their assigned network positions. We demonstrate the accuracy of the method using a cross-validated approach. In addition, we show that the method identifies a significant number of potential misannotations in Bacillus subtilis, including metabolic assignments already shown to be incorrect experimentally. The experimental analysis of the mispredicted genes forming the leucine degradation pathway in B. subtilis demonstrates that computational policing tools can generate important biological hypotheses.
authors: Center for Computational Biology and Bioinformatics and Department of Biomedical Informatics, Columbia University, Irving Cancer Research Center, New York, New York, USA.
authors: Tzu-Lin
authors: TL
authors: Hsiao
authors: Olga
authors: O
authors: Revelles
authors: Lifeng
authors: L
authors: Chen
authors: Uwe
authors: U
authors: Sauer
authors: Dennis
authors: D
authors: Vitkup
mesh_terms: D000465:Algorithms; D001331:Automation; D001412:Bacillus subtilis / Q000235:genetics* / Q000378:metabolism; D001671:Biochemistry / Q000379:methods*; D019295:Computational Biology / Q000379:methods*; D030541:Databases, Genetic; D001330:Electronic Data Processing; D023281:Genomics; D007930:Leucine / Q000737:chemistry; D008957:Models, Genetic; D015233:Models, Statistical; D010802:Phylogeny; D011786:Quality Control; D012372:ROC Curve; D012441:Saccharomyces cerevisiae / Q000235:genetics
chemical_list: D007930:Leucine