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
Link To Document :
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