Stochastic Assessment of Protein Databases by Generalized Entropy Measures

R. P. Mondaini () and S. C. de Albuquerque Neto
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R. P. Mondaini: Centre of Technology, COPPE, Federal University of Rio de Janeiro
S. C. de Albuquerque Neto: Centre of Technology, COPPE, Federal University of Rio de Janeiro

A chapter in Trends in Biomathematics: Modeling, Optimization and Computational Problems, 2018, pp 91-105 from Springer

Abstract: Abstract The organization of a sample space for studying the probability density functions whose temporal variation is able to describe the evolution of protein domains as registered in biological almanacs (protein databases) is done through two concurrent processes. The “poissonization” of a binomial process, and a multinomial process leading to a Gibbs–Shannon Entropy. The present approach is aimed to span the bridge across the difficulties of constructing a new theory which will be able to describe the function and evolution of protein families and their association into clans with the usual methods of Statistical Physics.

Keywords: Generalized Entropy Measures; Gibbs Shannon Entropy; Binomial Process; Master Demon; Simple Fokker-Planck Equation (search for similar items in EconPapers)
Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-319-91092-5_7

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DOI: 10.1007/978-3-319-91092-5_7

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