Predicting the phenotypic effects of non-synonymous single nucleotide polymorphisms based on support vector machines.

ABSTRACT:

Background

Human genetic variations primarily result from single nucleotide polymorphisms (SNPs) that occur approximately every 1000 bases in the overall human population. The non-synonymous SNPs (nsSNPs) that lead to amino acid changes in the protein product may account for nearly half of the known genetic variations linked to inherited human diseases. One of the key problems of medical genetics today is to identify nsSNPs that underlie disease-related phenotypes in humans. As such, the development of computational tools that can identify such nsSNPs would enhance our understanding of genetic diseases and help predict the disease.

Results

We propose a method, named Parepro (Predicting the amino acid replacement probability), to identify nsSNPs having either deleterious or n

SUBMITTER: Tian J 

PROVIDER: S-EPMC2216041 | biostudies-literature | 2007 Nov

REPOSITORIES: biostudies-literature