Codon adaptation index as a measure of dominating codon bias

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Codon adaptation index as a measure of dominating codon bias

UNLABELLED We propose a simple algorithm to detect dominating synonymous codon usage bias in genomes. The algorithm is based on a precise mathematical formulation of the problem that lead us to use the Codon Adaptation Index (CAI) as a 'universal' measure of codon bias. This measure has been previously employed in the specific context of translational bias. With the set of coding sequences as a...

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Relative Codon Adaptation Index, a Sensitive Measure of Codon Usage Bias

We propose a simple, sensitive measure of synonymous codon usage bias, the Relative Codon Adaptation Index (rCAI), as a way to discriminate better between highly biased and unbiased regions, compared with the widely used Codon Adaptation Index (CAI). CAI is a geometric mean of the relative usage of codons in a gene, and is calculated using the codon usage table trained with a set of highly expr...

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The codon Adaptation Index--a measure of directional synonymous codon usage bias, and its potential applications.

A simple, effective measure of synonymous codon usage bias, the Codon Adaptation Index, is detailed. The index uses a reference set of highly expressed genes from a species to assess the relative merits of each codon, and a score for a gene is calculated from the frequency of use of all codons in that gene. The index assesses the extent to which selection has been effective in moulding the patt...

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The development of codon bias indices (CBIs) remains an active field of research due to their myriad applications in computational biology. Recently, the relative codon usage bias (RCBS) was introduced as a novel CBI able to estimate codon bias without using a reference set. The results of this new index when applied to Escherichia coli and Saccharomyces cerevisiae led the authors of the origin...

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An Improved Implementation of Codon Adaptation Index

Codon adaptation index is a widely used index for characterizing gene expression in general and translation efficiency in particular. Current computational implementations have a number of problems leading to various systematic biases. I illustrate these problems and provide a better computer implementation to solve these problems. The improved CAI can predict protein production better than CAI...

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ژورنال

عنوان ژورنال: Bioinformatics

سال: 2003

ISSN: 1367-4803,1460-2059

DOI: 10.1093/bioinformatics/btg272