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CodonO: codon usage bias analysis within and across genomes

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 cod...

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Detalles Bibliográficos
Autores principales: Angellotti, Michael C., Bhuiyan, Shafquat B., Chen, Guorong, Wan, Xiu-Feng
Formato: Texto
Lenguaje:English
Publicado: Oxford University Press 2007
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1933134/
https://www.ncbi.nlm.nih.gov/pubmed/17537810
http://dx.doi.org/10.1093/nar/gkm392
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author Angellotti, Michael C.
Bhuiyan, Shafquat B.
Chen, Guorong
Wan, Xiu-Feng
author_facet Angellotti, Michael C.
Bhuiyan, Shafquat B.
Chen, Guorong
Wan, Xiu-Feng
author_sort Angellotti, Michael C.
collection PubMed
description 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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spelling pubmed-19331342007-07-31 CodonO: codon usage bias analysis within and across genomes Angellotti, Michael C. Bhuiyan, Shafquat B. Chen, Guorong Wan, Xiu-Feng Nucleic Acids Res Articles 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. Oxford University Press 2007-07 2007-05-30 /pmc/articles/PMC1933134/ /pubmed/17537810 http://dx.doi.org/10.1093/nar/gkm392 Text en © 2007 The Author(s) http://creativecommons.org/licenses/by-nc/2.0/uk/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Articles
Angellotti, Michael C.
Bhuiyan, Shafquat B.
Chen, Guorong
Wan, Xiu-Feng
CodonO: codon usage bias analysis within and across genomes
title CodonO: codon usage bias analysis within and across genomes
title_full CodonO: codon usage bias analysis within and across genomes
title_fullStr CodonO: codon usage bias analysis within and across genomes
title_full_unstemmed CodonO: codon usage bias analysis within and across genomes
title_short CodonO: codon usage bias analysis within and across genomes
title_sort codono: codon usage bias analysis within and across genomes
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1933134/
https://www.ncbi.nlm.nih.gov/pubmed/17537810
http://dx.doi.org/10.1093/nar/gkm392
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