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

Rinku Jain and S Ramakumar

Physica A: Statistical Mechanics and its Applications, 1999, vol. 273, issue 3, 476-485

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.

Keywords: Protein sequence length; Protein sequence evolution; Lognormal probability function; Random multiplicative process; Pareto's law (search for similar items in EconPapers)
Date: 1999
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:273:y:1999:i:3:p:476-485

DOI: 10.1016/S0378-4371(99)00370-2

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