Please use this identifier to cite or link to this item: https://doi.org/10.1142/S0219720007003090
Title: A gentle introduction to SNP analysis: Resources and tools
Authors: Mah, J.T.L.
Chia, K.S. 
Keywords: Complex disease
Nonsynonymous
Single nucleotide polymorphism
Issue Date: Oct-2007
Citation: Mah, J.T.L.,Chia, K.S. (2007-10). A gentle introduction to SNP analysis: Resources and tools. Journal of Bioinformatics and Computational Biology 5 (5) : 1123-1138. ScholarBank@NUS Repository. https://doi.org/10.1142/S0219720007003090
Abstract: Bioinformatics is the use of informatics tools and techniques in the study of molecular biology, genetic, or clinical data. The field of bioinformatics has expanded tremendously to cope with the large expansion of information generated by the mouse and human genome projects, as newer generations of computers that are much more powerful have emerged in the commercial market. It is now possible to employ the computing hardware and software at hand to generate novel methodologies in order to link data across the different databanks generated by these international projects and derive clinical and biological relevance from all of the information gathered. The ultimate goal would be to develop a computer program that can provide information correlating genes, their single nucleotide polymorphisms (SNPs), and the possible structural and functional effects on the encoded proteins with relation to known information on complex diseases with great ease and speed. Here, the recent developments of available software methods to analyze SNPs in relation to complex diseases are reviewed with emphasis on the type of predictions on protein structure and functions that can be made. The need for further development of comprehensive bioinformatics tools that can cope with information generated by the genomics communities is emphasized. © 2007 Imperial College Press.
Source Title: Journal of Bioinformatics and Computational Biology
URI: http://scholarbank.nus.edu.sg/handle/10635/109142
ISSN: 02197200
DOI: 10.1142/S0219720007003090
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