Selecton 2007: Advanced models for detecting positive and purifying selection using a Bayesian inference approach

Adi Stern, Adi Doron-Faigenboim, Elana Erez, Eric Martz, Eran Bacharach, Tal Pupko

Research output: Contribution to journalArticlepeer-review


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., 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.

Original languageEnglish
Pages (from-to)W506-W511
JournalNucleic Acids Research
Issue numberSUPPL.2
StatePublished - Jul 2007


Dive into the research topics of 'Selecton 2007: Advanced models for detecting positive and purifying selection using a Bayesian inference approach'. Together they form a unique fingerprint.

Cite this