Literature DB >> 28163008

The information capacity of the genetic code: Is the natural code optimal?

Ercan E Kuruoglu1, Peter F Arndt2.   

Abstract

We envision the molecular evolution process as an information transfer process and provide a quantitative measure for information preservation in terms of the channel capacity according to the channel coding theorem of Shannon. We calculate Information capacities of DNA on the nucleotide (for non-coding DNA) and the amino acid (for coding DNA) level using various substitution models. We extend our results on coding DNA to a discussion about the optimality of the natural codon-amino acid code. We provide the results of an adaptive search algorithm in the code domain and demonstrate the existence of a large number of genetic codes with higher information capacity. Our results support the hypothesis of an ancient extension from a 2-nucleotide codon to the current 3-nucleotide codon code to encode the various amino acids.
Copyright © 2017 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  DNA; Genetic code; Information capacity; Information theory; Shannon theory

Mesh:

Substances:

Year:  2017        PMID: 28163008     DOI: 10.1016/j.jtbi.2017.01.046

Source DB:  PubMed          Journal:  J Theor Biol        ISSN: 0022-5193            Impact factor:   2.691


  2 in total

1.  Frameshift and wild-type proteins are often highly similar because the genetic code and genomes were optimized for frameshift tolerance.

Authors:  Xiaolong Wang; Quanjiang Dong; Gang Chen; Jianye Zhang; Yongqiang Liu; Yujia Cai
Journal:  BMC Genomics       Date:  2022-06-02       Impact factor: 4.547

2.  Neural Network Structure Optimization by Simulated Annealing.

Authors:  Chun Lin Kuo; Ercan Engin Kuruoglu; Wai Kin Victor Chan
Journal:  Entropy (Basel)       Date:  2022-02-28       Impact factor: 2.524

  2 in total

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