Table 2 Methods for predicting the consequences of point mutations

SIFT

http://sift.jcvi.org

Uses sequence homology scores that are calculated using position-specific scoring matrices with Dirichlet priors

Polyphen 2

http://genetics.bwh.harvard.edu/pph2/

Uses sequence conservation, structure and Swiss-Prot annotations

PMUT

http://mmb2.pcb.ub.es:8080/PMut/

Formulates predictions with neural networks, using internal databases, secondary structure prediction and sequence conservation

SNPs3D

http://www.snps3d.org/

Based on a support vector machine that uses structural or sequence conservation parameters

PantherPSEC19

http://www.pantherdb.org/tools/csnpScoreForm.jsp

Uses sequence homology scores calculated using PANTHER hidden Markov model families

Mutationassessor

http://mutationassessor.org

Provides predictions using additional information based on the specific patterns of conservation of protein families

VEP (Variant Effect Predictor)

http://www.ensembl.org/info/docs/variation/vep

This system categorizes Ensembl genomic variants in known transcripts by their potential effect

KinMut

http://kinmut.bioinfo.cnio.es

Prediction of the consequences of mutations in protein kinases; the system was trained with specific information about the kinase subfamilies, and together with the predictions provides general information about the corresponding proteins, a comparison with other predictors and links to the related literature