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Computational Methods to Work as First-Pass Filter in Deleterious SNP Analysis of Alkaptonuria
Author(s) -
R. Magesh,
C. George Priya Doss
Publication year - 2012
Publication title -
the scientific world journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.453
H-Index - 93
eISSN - 2356-6140
pISSN - 1537-744X
DOI - 10.1100/2012/738423
Subject(s) - in silico , alkaptonuria , snp , context (archaeology) , computational biology , single nucleotide polymorphism , functional genomics , human genetic variation , genetics , genetic variants , genomics , computer science , biology , bioinformatics , human genome , gene , genome , genotype , paleontology
A major challenge in the analysis of human genetic variation is to distinguish functional from nonfunctional SNPs. Discovering these functional SNPs is one of the main goals of modern genetics and genomics studies. There is a need to effectively and efficiently identify functionally important nsSNPs which may be deleterious or disease causing and to identify their molecular effects. The prediction of phenotype of nsSNPs by computational analysis may provide a good way to explore the function of nsSNPs and its relationship with susceptibility to disease. In this context, we surveyed and compared variation databases along with in silico prediction programs to assess the effects of deleterious functional variants on protein functions. In other respects, we attempted these methods to work as first-pass filter to identify the deleterious substitutions worth pursuing for further experimental research. In this analysis, we used the existing computational methods to explore the mutation-structure-function relationship in HGD gene causing alkaptonuria.

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