nsSNPAnalyzer: identifying disease-associated nonsynonymous single nucleotide polymorphisms

Nucleic Acids Res. 2005 Jul 1;33(Web Server issue):W480-2. doi: 10.1093/nar/gki372.


Nonsynonymous single nucleotide polymorphisms (nsSNPs) are prevalent in genomes and are closely associated with inherited diseases. To facilitate identifying disease-associated nsSNPs from a large number of neutral nsSNPs, it is important to develop computational tools to predict the nsSNP's phenotypic effect (disease-associated versus neutral). nsSNPAnalyzer, a web-based software developed for this purpose, extracts structural and evolutionary information from a query nsSNP and uses a machine learning method called Random Forest to predict the nsSNP's phenotypic effect. nsSNPAnalyzer server is available at http://snpanalyzer.utmem.edu/.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Artificial Intelligence
  • Computational Biology
  • Genetic Predisposition to Disease*
  • Humans
  • Internet
  • Phenotype
  • Polymorphism, Single Nucleotide*
  • Protein Conformation
  • Sequence Alignment
  • Sequence Analysis, Protein / methods*
  • Software*
  • User-Computer Interface