DocumentCode
1060927
Title
Information-Theoretic Model of Evolution over Protein Communication Channel
Author
Gong, Liuling ; Bouaynaya, Nidhal ; Schonfeld, Dan
Author_Institution
Dept. of Electr. & Comput. Eng., Univ. of Illinois at Chicago, Chicago, IL, USA
Volume
8
Issue
1
fYear
2011
Firstpage
143
Lastpage
151
Abstract
In this paper, we propose a communication model of evolution and investigate its information-theoretic bounds. The process of evolution is modeled as the retransmission of information over a protein communication channel, where the transmitted message is the organism´s proteome encoded in the DNA. We compute the capacity and the rate distortion functions of the protein communication system for the three domains of life: Archaea, Bacteria, and Eukaryotes. The tradeoff between the transmission rate and the distortion in noisy protein communication channels is analyzed. As expected, comparison between the optimal transmission rate and the channel capacity indicates that the biological fidelity does not reach the Shannon optimal distortion. However, the relationship between the channel capacity and rate distortion achieved for different biological domains provides tremendous insight into the dynamics of the evolutionary processes of the three domains of life. We rely on these results to provide a model of genome sequence evolution based on the two major evolutionary driving forces: mutations and unequal crossovers.
Keywords
bioinformatics; evolution (biological); microorganisms; proteins; Archaea; Bacteria; DNA; Eukaryote; Shannon optimal distortion; evolution; information theoretic model; protein communication channel; rate distortion function; Archaea; Biological information theory; Channel capacity; Communication channels; DNA; Evolution (biology); Microorganisms; Proteins; Rate distortion theory; Rate-distortion; Protein communication system; channel capacity; nonhomogeneous Poisson process.; rate distortion theory; Algorithms; Computational Biology; Crossing Over, Genetic; Evolution, Molecular; Information Theory; Markov Chains; Models, Biological; Mutation; Poisson Distribution; Proteins; Proteome; Signal Transduction;
fLanguage
English
Journal_Title
Computational Biology and Bioinformatics, IEEE/ACM Transactions on
Publisher
ieee
ISSN
1545-5963
Type
jour
DOI
10.1109/TCBB.2009.1
Filename
4745630
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