Abstract
Synonymous codon usage biases are associated with various biological factors, such as gene expression level, gene length, gene translation initiation signal, protein amino acid composition, protein structure, tRNA abundance, mutation frequency and patterns, and GC compositions. Quantification of codon usage bias helps understand evolution of living organisms. A codon usage bias pipeline is demanding for codon usage bias analyses within and across genomes. Here we present a CodonO webserver service as a user-friendly tool for codon usage bias analyses across and within genomes in real time. The webserver is available at http//www.sysbiology.org/CodonO. Contact: wanhenry@yahoo.com.
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