A Genetic Optimization Approach for Isolating Translational Efficiency Bias

TitleA Genetic Optimization Approach for Isolating Translational Efficiency Bias
Publication TypeJournal Article
Year of Publication2008
AuthorsD. Raiford, Doug Raiford, Dan Krane, Travis Doom, Michael Raymer
JournalIEEE Control Systems Society
Keywordscodon usage bias, Evolutionary computing and genetic algorithms, GC-content, strand bias, translational efficiency

The study of codon usage bias is an important research area that contributes to our understanding of molecular evolution, phylogenetic relationships, respiratory lifestyle, and other characteristics. Translational efficiency bias is perhaps the most well studied codon usage bias, as it is frequently utilized to predict relative protein expression levels. We present a novel approach to isolating translational efficiency bias in microbial genomes. There are several existent methods for isolating translational efficiency bias. Previous approaches are susceptible to the confounding influences of other potentially dominant biases. Additionally, existing approaches to identifying translational efficiency bias generally require both genomic sequence information and prior knowledge of a set of highly expressed genes. This novel approach provides more accurate results from sequence information alone by resisting the confounding effects of other biases. We validate this increase in accuracy in isolating translational efficiency bias on ten microbial genomes, five of which have proven particularly difficult for existing approaches due to the presence of strong confounding biases.

Full Text

Doug Raiford,Dan Krane,Travis Doom,Michael Raymer A Genetic Optimization Approach for Isolating Translational Efficiency Bias
research center: Kno.e.sis Center
publisher: IEEE Control Systems Society
year: 2009