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Article Number - 60FC53E48559


Vol.6(1), pp. 1-14 , November 2014
DOI: 10.5897/JCBBR2014.0102
ISSN: 2141-2227



Full Length Research Paper

Development of genodynamic metrics for exploring the biophysics of DNA polymorphisms



James Lindesay
  • James Lindesay
  • Computational Physics Laboratory, Department of Physics and Astronomy, Howard University, Washington, DC, 20059, U.S
  • Google Scholar
Tshela E Mason
  • Tshela E Mason
  • National Human Genome Center, Howard University, Washington, DC, 20060, U.S
  • Google Scholar
William Hercules
  • William Hercules
  • Computational Physics Laboratory, Department of Physics and Astronomy, Howard University, Washington, DC, 20059, U.S
  • Google Scholar
Georgia M Dunston*
  • Georgia M Dunston*
  • 2. National Human Genome Center, Howard University, Washington, DC, 20060, U.S; 3. Department of Microbiology, Howard University, Washington, DC, 20059, U.S.
  • Google Scholar







 Received: 19 March 2014  Accepted: 02 September 2014  Published: 30 November 2014

Copyright © 2014 Author(s) retain the copyright of this article.
This article is published under the terms of the Creative Commons Attribution License 4.0


Single nucleotide polymorphisms (SNPs) represent an important type of dynamic sites within the human genome. These common variants often locally correlate within more complex multi-SNP haploblocks that are maintained throughout generations in a stable population. Information encoded in the structure of SNPs and SNP haploblock variation can be characterized through a normalized information content metric. Genodynamics is being developed as the analogous “thermodynamics” characterizing the state variables for genomic populations that are stable under stochastic environmental stresses. Since living systems have not been found to develop in the absence of environmental influences, this paper describes the analogous genomic free energy metrics in a given environment. SNP haploblocks were constructed by Haploview v4.2 for five chromosomes from phase III HapMap data, and the genomic state variables for each chromosome were calculated. An in silico analysis was performed on SNP haploblocks with the lowest genomic energy measures. Highly favorable genomic energy measures were found to correlate with highly conserved SNP haploblocks. Moreover, the most conserved haploblocks were associated with an evolutionarily conserved regulatory element and domain.

Key words: Information theory, entropy, genomic variation, biological information, genodynamics.

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APA Lindesay, J., Mason, T. E., Hercules, W., & Dunston, G. M. (2014). Development of genodynamic metrics for exploring the biophysics of DNA polymorphisms. Journal of Computational Biology and Bioinformatics Research, 6(1), 1-14.
Chicago James Lindesay, Tshela E Mason, William Hercules and Georgia M Dunston,. "Development of genodynamic metrics for exploring the biophysics of DNA polymorphisms." Journal of Computational Biology and Bioinformatics Research 6, no. 1 (2014): 1-14.
MLA James Lindesay, et al. "Development of genodynamic metrics for exploring the biophysics of DNA polymorphisms." Journal of Computational Biology and Bioinformatics Research 6.1 (2014): 1-14.
   
DOI 10.5897/JCBBR2014.0102
URL http://academicjournals.org/journal/JCBBR/article-abstract/60FC53E48559

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