Statistical distributions and entropy considerations in gene codes

TL;DR

This paper explores the statistical and information-theoretic properties of gene codes, highlighting hyperbolic distributions, entropy considerations, and similarities between gene length histograms and language words, supported by genomic data.

Contribution

It introduces a theoretical framework linking hyperbolic distributions to entropy stability in gene codes and correlates these with empirical genomic data.

Findings

Gene length histograms resemble language word distributions

Hyperbolic distributions imply entropy loss and stability in genomes

Empirical data from multiple species support the theory

Abstract

In our paper selected linguistic features of genomes to study the statistics of the gene codes are considered. We present the information theory from which it follows that if the system is described by distributions of hyperbolic type it leads to the possibility of entropy loss and stability. We show that the histograms of gene lengths are similar to that of language words. We show the correspondence between presented theory and results for the number of replicated genes and replicated fragments of genes in genomes for Borelia burgdorferi, Escherichia coli and Saccharomyces cerevisiae S288c.