Computational SNP analysis: current approaches and future prospects

Ambuj Kumar, Vidya Rajendran, Rao Sethumadhavan, Priyank Shukla, Shalinee Tiwari, Rituraj Purohit

Research output: Contribution to journalArticlepeer-review

40 Citations (Scopus)


The computational approaches in determining disease-associated Non-synonymous single nucleotide polymorphisms (nsSNPs) have evolved very rapidly. Large number of deleterious and disease-associated nsSNP detection tools have been developed in last decade showing high prediction reliability. Despite of all these highly efficient tools, we still lack the accuracy level in determining the genotype-phenotype association of predicted nsSNPs. Furthermore, there are enormous questions that are yet to be computationally compiled before we might talk about the prediction accuracy. Earlier we have incorporated molecular dynamics simulation approaches to foster the accuracy level of computational nsSNP analysis road map, which further helped us to determine the changes in the protein phenotype associated with the computationally predicted disease-associated mutation. Here we have discussed on the present scenario of computational nsSNP characterization technique and some of the questions that are crucial for the proper understanding of pathogenicity level for any disease associated mutations.
Original languageEnglish
Pages (from-to)233-239
JournalCell Biochemistry and Biophysics
Issue number2
Early online date13 Jul 2013
Publication statusPublished online - 13 Jul 2013


  • nsSNPs
  • Onco-allele
  • Oncogene
  • Molecular dynamics simulation
  • SNP-Calling
  • Bioinformatics


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