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Selecton 2007: Advanced models for detecting positive and purifying selection using a Bayesian inference approach
Year:
2007
Source of publication :
Nucleic Acids Research
Authors :
Doron-Faigenboim, Adi
;
.
Volume :
35
Co-Authors:
Stern, A., Department of Cell Research and Immunology, George S. Wise Faculty of Life Sciences, Tel Aviv University, Ramat Aviv 69978, Israel
Doron-Faigenboim, A., Department of Cell Research and Immunology, George S. Wise Faculty of Life Sciences, Tel Aviv University, Ramat Aviv 69978, Israel
Erez, E., Department of Cell Research and Immunology, George S. Wise Faculty of Life Sciences, Tel Aviv University, Ramat Aviv 69978, Israel
Martz, E., Department of Microbiology, University of Massachusetts, Amherst, MA 01003, United States
Bacharach, E., Department of Cell Research and Immunology, George S. Wise Faculty of Life Sciences, Tel Aviv University, Ramat Aviv 69978, Israel
Pupko, T., Department of Cell Research and Immunology, George S. Wise Faculty of Life Sciences, Tel Aviv University, Ramat Aviv 69978, Israel
Facilitators :
From page:
To page:
(
Total pages:
1
)
Abstract:
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 (u) 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 mechanisticempirical 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. © 2007 The Author(s).
Note:
Related Files :
Amino Acids
Animal
Animals
computer simulation
Genetics
Internet
Models, Molecular
molecular genetics
proteins
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Related Content
More details
DOI :
10.1093/nar/gkm382
Article number:
Affiliations:
Database:
Scopus
Publication Type:
article
;
.
Language:
English
Editors' remarks:
ID:
28422
Last updated date:
02/03/2022 17:27
Creation date:
17/04/2018 00:39
Scientific Publication
Selecton 2007: Advanced models for detecting positive and purifying selection using a Bayesian inference approach
35
Stern, A., Department of Cell Research and Immunology, George S. Wise Faculty of Life Sciences, Tel Aviv University, Ramat Aviv 69978, Israel
Doron-Faigenboim, A., Department of Cell Research and Immunology, George S. Wise Faculty of Life Sciences, Tel Aviv University, Ramat Aviv 69978, Israel
Erez, E., Department of Cell Research and Immunology, George S. Wise Faculty of Life Sciences, Tel Aviv University, Ramat Aviv 69978, Israel
Martz, E., Department of Microbiology, University of Massachusetts, Amherst, MA 01003, United States
Bacharach, E., Department of Cell Research and Immunology, George S. Wise Faculty of Life Sciences, Tel Aviv University, Ramat Aviv 69978, Israel
Pupko, T., Department of Cell Research and Immunology, George S. Wise Faculty of Life Sciences, Tel Aviv University, Ramat Aviv 69978, Israel
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. bioinfo.tau.ac.il), a web server which automatically calculates the ratio between K a and K s (u) 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 mechanisticempirical 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. © 2007 The Author(s).
Scientific Publication
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