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Computational Analysis of SNPs in 10 kb Region of Human Chromosome 1 | OMICS International | Abstract
ISSN: 0974-7230

Journal of Computer Science & Systems Biology
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Research Article

Computational Analysis of SNPs in 10 kb Region of Human Chromosome 1

Gupta Manish Kumar1*, Nutan Prakash2, Chaturvedi Pragya3 and Misra Krishna3

1Department of Bioinformatics, University Institute of Engineering and Technology, Chhatrapati Shahu Ji Maharaj University, Kanpur -208024, India

2Department of Biotechnology, Shree M & N Virani Science College, Rajkot, Gujarat

3Center of Biomedical Magnetic Resonance, SGPGIMS, Luck now-India

*Corresponding Author:
Dr. Gupta Manish Kumar
Department of Bioinformatics
University Institute of Engineering and Technology
Chhatrapati Shahu Ji Maharaj University
Kanpur -208024, India
E-mail: [email protected]

Received March 22, 2011; Accepted April 12, 2011; Published April 14, 2011

Citation: Kumar GM, Prakash N, Pragya C, Krishna M (2011) Computational Analysis of SNPs in 10 kb Region of Human Chromosome 1. J Comput Sci Syst Biol 4:033-034. doi:10.4172/jcsb.1000073

Copyright: © 2011 Kumar GM, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License,which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.


As a result of human genome project a large burst of genomic data comes. Researchers are trying to correlate this sequenced data to find out variations, which will help to study the effect of variations on disease progression. Single nucleotide polymorphism is one of the genetic markers which are most widely used in genetic association studies of a population. SNPs are DNA sequence variations that occur when a single nucleotide (A, T, C, or G) in the genome sequence is altered. SNPs found within a coding sequence are of particular interest to researchers because they are more likely to alter the biological function of a protein. Occasionally, SNPs can cause disease and can be used to search and isolate diseased gene. The SNPs found in this region and its linkage disequilibrium analysis to find out the effect of SNPs found and there correlation. However it is much easier, cheaper and faster than in vitro analysis, computational analysis will provide an insight to probable disease causing SNPs having some functional value which can be assayed in vitro. Present computational analysis is to find out SNPs in the chromosome 1.


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