Literature DB >> 6871390

Noise immunity of the genetic code.

G Cullmann, J M Labouygues.   

Abstract

Error detection and correction properties are fundamental for informative codes. Hamming's distance allows us to study this noise resistance. We present codes characterized by the resistance optimization to nonsense mutational effects. The calculation of the cumulated Hamming's distance allowing to determine the number of optimal codes and their structure can be detailed. The principle of these laws of optimization of resistance consists of choosing constituent codons connected by mutational neighbouring in such a way that random application of mutations on such a code minimize the occurrence of nonsense n-uplets or terminators. New coding symmetries are then described and screened using Galois's polynomials properties and Baudot's code. Such a study can be applied to any length of the codons. Here we present the principles of this optimization for the most simple doublet codes. Another constraint is discussed: the distribution of optimal subcodes for synonymity and the frequencies of utilization of the different codons. We compare these results to those of the present genetic code, and we observe that all coded amino acids (except the particular case of SER) are using optimal sub-codes of synonymity. This work suggests that the appearance of the genetic code was provoked by mutations while optimizing on several levels its resistance to their effects. Thus genetic coding would have been the best automata that could be produced in prebiotic conditions.

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Year:  1983        PMID: 6871390     DOI: 10.1016/0303-2647(83)90022-9

Source DB:  PubMed          Journal:  Biosystems        ISSN: 0303-2647            Impact factor:   1.973


  5 in total

Review 1.  The case for an error minimizing standard genetic code.

Authors:  Stephen J Freeland; Tao Wu; Nick Keulmann
Journal:  Orig Life Evol Biosph       Date:  2003-10       Impact factor: 1.950

2.  The Standard Genetic Code Facilitates Exploration of the Space of Functional Nucleotide Sequences.

Authors:  Shubham Tripathi; Michael W Deem
Journal:  J Mol Evol       Date:  2018-06-29       Impact factor: 2.395

3.  Optimization and the genetic code.

Authors:  A Figureau
Journal:  Orig Life Evol Biosph       Date:  1989       Impact factor: 1.950

4.  Information theory and the genetic code.

Authors:  A Figureau
Journal:  Orig Life Evol Biosph       Date:  1987       Impact factor: 1.950

5.  The mathematical logic of life.

Authors:  G Cullmann; J M Labouygues
Journal:  Orig Life       Date:  1984
  5 in total

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