Stochastic dynamics modeling of the protein sequence length distribution in genomes: implications for microbial evolution

Jain, Rinku and Ramakumar, S (1999) Stochastic dynamics modeling of the protein sequence length distribution in genomes: implications for microbial evolution. In: Physica A: Statistical Mechanics and its Applications, 273 (3-4). pp. 476-485.

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Abstract

In this paper, we report an analysis of the protein sequence length distribution for 13 bacteria, four archaea and one eukaryote whose genomes have been completely sequenced, The frequency distribution of protein sequence length for all the 18 organisms are remarkably similar, independent of genome size and can be described in terms of a lognormal probability distribution function. A simple stochastic model based on multiplicative processes has been proposed to explain the sequence length distribution. The stochastic model supports the random-origin hypothesis of protein sequences in genomes. Distributions of large proteins deviate from the overall lognormal behavior. Their cumulative distribution follows a power-law analogous to Pareto's law used to describe the income distribution of the wealthy. The protein sequence length distribution in genomes of organisms has important implications for microbial evolution and applications. (C) 1999 Elsevier Science B.V. All rights reserved.

Item Type:	Journal Article
Publication:	Physica A: Statistical Mechanics and its Applications
Publisher:	Elsevier Science
Additional Information:	Copyright of this article belongs to Elsevier Science.
Keywords:	Protein sequence length;Protein sequence evolution;Lognormal probability function;Random multiplicative process;Pareto's law
Department/Centre:	Division of Information Sciences (Doesn't exist now) > BioInformatics Centre Division of Physical & Mathematical Sciences > Physics
Date Deposited:	30 Jun 2011 07:50
Last Modified:	30 Jun 2011 07:50
URI:	http://eprints.iisc.ac.in/id/eprint/38793

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