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Selecton 2007: advanced models for detecting positive and purifying selection using a Bayesian inference approach
Biologically significant sites in a protein may be identified by contrasting the rates of synonymous (K(s)) and non-synonymous (K(a)) substitutions. This enables the inference of site-specific positive Darwinian selection and purifying selection. We present here Selecton version 2.2 (http://selecton...
Autores principales: | , , , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2007
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1933148/ https://www.ncbi.nlm.nih.gov/pubmed/17586822 http://dx.doi.org/10.1093/nar/gkm382 |
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author | Stern, Adi Doron-Faigenboim, Adi Erez, Elana Martz, Eric Bacharach, Eran Pupko, Tal |
author_facet | Stern, Adi Doron-Faigenboim, Adi Erez, Elana Martz, Eric Bacharach, Eran Pupko, Tal |
author_sort | Stern, Adi |
collection | PubMed |
description | Biologically significant sites in a protein may be identified by contrasting the rates of synonymous (K(s)) and non-synonymous (K(a)) substitutions. This enables the inference of site-specific positive Darwinian selection and purifying selection. We present here Selecton version 2.2 (http://selecton.bioinfo.tau.ac.il), a web server which automatically calculates the ratio between K(a) and K(s) (ω) at each site of the protein. This ratio is graphically displayed on each site using a color-coding scheme, indicating either positive selection, purifying selection or lack of selection. Selecton implements an assembly of different evolutionary models, which allow for statistical testing of the hypothesis that a protein has undergone positive selection. Specifically, the recently developed mechanistic-empirical model is introduced, which takes into account the physicochemical properties of amino acids. Advanced options were introduced to allow maximal fine tuning of the server to the user's specific needs, including calculation of statistical support of the ω values, an advanced graphic display of the protein's 3-dimensional structure, use of different genetic codes and inputting of a pre-built phylogenetic tree. Selecton version 2.2 is an effective, user-friendly and freely available web server which implements up-to-date methods for computing site-specific selection forces, and the visualization of these forces on the protein's sequence and structure. |
format | Text |
id | pubmed-1933148 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2007 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-19331482007-07-31 Selecton 2007: advanced models for detecting positive and purifying selection using a Bayesian inference approach Stern, Adi Doron-Faigenboim, Adi Erez, Elana Martz, Eric Bacharach, Eran Pupko, Tal Nucleic Acids Res Articles Biologically significant sites in a protein may be identified by contrasting the rates of synonymous (K(s)) and non-synonymous (K(a)) substitutions. This enables the inference of site-specific positive Darwinian selection and purifying selection. We present here Selecton version 2.2 (http://selecton.bioinfo.tau.ac.il), a web server which automatically calculates the ratio between K(a) and K(s) (ω) at each site of the protein. This ratio is graphically displayed on each site using a color-coding scheme, indicating either positive selection, purifying selection or lack of selection. Selecton implements an assembly of different evolutionary models, which allow for statistical testing of the hypothesis that a protein has undergone positive selection. Specifically, the recently developed mechanistic-empirical model is introduced, which takes into account the physicochemical properties of amino acids. Advanced options were introduced to allow maximal fine tuning of the server to the user's specific needs, including calculation of statistical support of the ω values, an advanced graphic display of the protein's 3-dimensional structure, use of different genetic codes and inputting of a pre-built phylogenetic tree. Selecton version 2.2 is an effective, user-friendly and freely available web server which implements up-to-date methods for computing site-specific selection forces, and the visualization of these forces on the protein's sequence and structure. Oxford University Press 2007-07 2007-06-22 /pmc/articles/PMC1933148/ /pubmed/17586822 http://dx.doi.org/10.1093/nar/gkm382 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 Stern, Adi Doron-Faigenboim, Adi Erez, Elana Martz, Eric Bacharach, Eran Pupko, Tal Selecton 2007: advanced models for detecting positive and purifying selection using a Bayesian inference approach |
title | Selecton 2007: advanced models for detecting positive and purifying selection using a Bayesian inference approach |
title_full | Selecton 2007: advanced models for detecting positive and purifying selection using a Bayesian inference approach |
title_fullStr | Selecton 2007: advanced models for detecting positive and purifying selection using a Bayesian inference approach |
title_full_unstemmed | Selecton 2007: advanced models for detecting positive and purifying selection using a Bayesian inference approach |
title_short | Selecton 2007: advanced models for detecting positive and purifying selection using a Bayesian inference approach |
title_sort | selecton 2007: advanced models for detecting positive and purifying selection using a bayesian inference approach |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1933148/ https://www.ncbi.nlm.nih.gov/pubmed/17586822 http://dx.doi.org/10.1093/nar/gkm382 |
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