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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...
Autores principales: | , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2007
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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. |
format | Text |
id | pubmed-1933134 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2007 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
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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