Literature DB >> 16538284

On genetic information, diversity and distance.

J Zvárová1, I Vajda.   

Abstract

OBJECTIVES: General information-theoretic concepts such as f-divergence, f-information and f-entropy are applied to the genetic models where genes are characterized by randomly distributed alleles. The paper thus presents an information-theoretic background for measuring genetic distances between populations, genetic information in various observations on individuals about their alleles and, finally, genetic diversities in various populations.
METHODS: Genetic distances were derived as divergences between frequencies of alleles representing a gene in two different populations. Genetic information was derived as a measure of statistical association between the observations taken on individuals and the alleles of these individuals. Genetic diversities were derived from divergences and information.
RESULTS: The concept of genetic f-information introduced in the paper seems to be new. We show that the measures of genetic distance and diversity used in the previous literature are special cases of the genetic f-divergence and f-diversity introduced in the paper and illustrated by examples. We also display intimate connections between the genetic f-information and the genetic f-divergence on one side and genetic f-diversity on the other side. The examples at the same time also illustrate practical computations and applications of the important concepts of quantitative genetics introduced in the paper.
CONCLUSIONS: We discussed a general class of f- divergence measures that are suitable measures of genetic distance between populations characterized by concrete frequencies of alleles. We have shown that a wide class of genetic information, called f-information, can be obtained from f-divergences and that a wide class of measures of genetic diversity, called f-diversities, can be obtained from the f-divergences and f-information.

Mesh:

Year:  2006        PMID: 16538284

Source DB:  PubMed          Journal:  Methods Inf Med        ISSN: 0026-1270            Impact factor:   2.176


  1 in total

1.  Measuring diversity in medical reports based on categorized attributes and international classification systems.

Authors:  Petra Přečková; Jana Zvárová; Karel Zvára
Journal:  BMC Med Inform Decis Mak       Date:  2012-04-12       Impact factor: 2.796

  1 in total

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