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Title: Assessment of genome annotation using gene function similarity within the gene neighborhood

Journal Article · · BMC Bioinformatics
ORCiD logo [1];  [1];  [2];  [2]
  1. Univ. of Arkansas for Medical Sciences, Little Rock, AR (United States)
  2. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

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. Conclusions: 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.

Research Organization:
Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
Sponsoring Organization:
USDOE Office of Science (SC), Biological and Environmental Research (BER)
Grant/Contract Number:
AC05-00OR22725
OSTI ID:
1626764
Journal Information:
BMC Bioinformatics, Vol. 18, Issue 1; ISSN 1471-2105
Publisher:
BioMed CentralCopyright Statement
Country of Publication:
United States
Language:
English

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Cited By (2)



Figures / Tables (6)