Single Nucleotide Polymorphisms: A Window into the Informatics of the Living Genome


Nested in the environment of the nucleus of the cell, the 23 sets of chromosomes that comprise the human genome function as one integrated whole system, orchestrating the expression of thousands of genes underlying the biological characteristics of the cell, individual and the species. The extraction of meaningful information from this complex data set depends crucially upon the lens through which the data are examined. We present a biophysical perspective on genomic information encoded in single nucleotide polymorphisms (SNPs), and introduce metrics for modeling information encoded in the genome. Information, like energy, is considered to be a conserved physical property of the universe. The information structured in SNPs describes the adaptation of a human population to a given environment. The maintained order measured by the information content is associated with entropies, energies, and other state variables for a dynamic system in homeostasis. “Genodynamics” characterizes the state variables for genomic populations that are stable under stochastic environmental stresses. The determination of allelic energies allows the parameterization of specific environmental influences upon individual alleles across populations. The environment drives population-based genome variation. From this vantage point, the genome is modeled as a complex, dynamic information system defined by patterns of SNP alleles and SNP haplotypes.

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Dunston, G. , Mason, T. , Hercules, W. and Lindesay, J. (2014) Single Nucleotide Polymorphisms: A Window into the Informatics of the Living Genome. Advances in Bioscience and Biotechnology, 5, 623-626. doi: 10.4236/abb.2014.57073.

Conflicts of Interest

The authors declare no conflicts of interest.


[1] Lindesay, J., Mason, T.E., Ricks-Santi, L., Hercules, W., Kurian, P. and Dunston, G.M. (2012) A New Biophysical Metric for Interrogating the Information Content in Human Genome Sequence Variation: Proof of Concept. Journal of Computational Biology and Bioinformatics Research, 4, 15-22.
[2] Lindesay, J., Mason, T.E., Hercules, W. and Dunston, G.M. (2013) The Foundations of Genodynamics: The Development of Metrics for Genomic-Environmental Interactions.

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