Information Theories in Molecular Biology and Genomics

Andrzej K Konopka, BioLingua Research Inc.– Center for Advanced Sequence Analysis, Gaithersburg, Maryland, USA

Published online: January 2006

DOI: 10.1038/npg.els.0005927

Information theory, statistical theory of signal transmission, communication theory and Shannon theory are synonymous names for the mathematical theory first published by Claude Shannon in the 1940s. The concept of entropy in this theory can be viewed as a measure of ‘randomness’ of sequences of symbols. Shannon entropy and its variants have been widely used in molecular biology and bioinformatics as statistical tools of choice for sequence and structure analyses.

Keywords: Shannon communication theory; information; probability; coding; sequence analysis; cryptanalysis; uniform distribution

Figure 1. Meanings of ‘information’ in biology. A view from the perspective of the machine metaphor. A clearly reductionist view of living things based on the machine metaphor leads to two different general concepts of ‘information’. Each of these concepts has a different rationale and implicit meaning derived from it. Only a very few aspects of these meanings can be modeled by Shannon theory (these are indicated by the symbol *SH* on the diagram).
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Related Sub-Topics:

Protein Folding, Evolution and Degradation | Bioinformatics | Techniques and Tools in Clinical Genetics | Statistical Methodology in Genetics | Bioinformatics and Genetic Disease | Techniques and Tools in Molecular Biology | Computational Molecular Biology
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Article Title: Information Theories in Molecular Biology and Genomics
 
How to Cite close
Konopka, Andrzej K(Jan 2006) Information Theories in Molecular Biology and Genomics. In: eLS. John Wiley & Sons Ltd, Chichester. http://www.els.net [doi: 10.1038/npg.els.0005927]