Literature DB >> 940172

Simulation studies on the evolution of amino acid sequences.

T Ohta.   

Abstract

A model of molecular evolution in which the parameter (intrinsic rate of amino acid substitution) fluctuates from time to time was investigated by simulating the process. It was found that the usual method of estimation such as Poisson fitting underestimates this variation of the parameter when remote comparisons are made. At the same time, four distance measures (minimun base difference, Poisson fitting, random nucleotide substitutions and negative binomial fitting) were tested for their accuracy. When the substitution rate is not uniform among the amino acid sites, the negative bionomial fitting gives most satisfactory results, however, one needs to know the parameter beforehand in order to use this method. It was pointed out that the fluctuation of the evolutionary rate is expected if the nearly neutral but very slightly deleterious mutations play an important role on molecular evolution.

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Year:  1976        PMID: 940172     DOI: 10.1007/bf01738879

Source DB:  PubMed          Journal:  J Mol Evol        ISSN: 0022-2844            Impact factor:   2.395


  16 in total

Review 1.  Darwinian evolution in the genealogy of haemoglobin.

Authors:  M Goodman; G W Moore; G Matsuda
Journal:  Nature       Date:  1975-02-20       Impact factor: 49.962

2.  Theoretical foundations for a quantitative approach to paleogenetics : Part II: Proteins.

Authors:  R Holmquist
Journal:  J Mol Evol       Date:  1972-06       Impact factor: 2.395

3.  Slightly deleterious mutant substitutions in evolution.

Authors:  T Ohta
Journal:  Nature       Date:  1973-11-09       Impact factor: 49.962

4.  An examination of the constancy of the rate of molecular evolution.

Authors:  C H Langley; W M Fitch
Journal:  J Mol Evol       Date:  1974       Impact factor: 2.395

5.  Molecular evolution as predicted by natural selection.

Authors:  L Van Valen
Journal:  J Mol Evol       Date:  1974       Impact factor: 2.395

6.  Amino acid difference formula to help explain protein evolution.

Authors:  R Grantham
Journal:  Science       Date:  1974-09-06       Impact factor: 47.728

7.  Evolutionary rate at the molecular level.

Authors:  M Kimura
Journal:  Nature       Date:  1968-02-17       Impact factor: 49.962

Review 8.  Construction of phylogenetic trees.

Authors:  W M Fitch; E Margoliash
Journal:  Science       Date:  1967-01-20       Impact factor: 47.728

9.  The rate of molecular evolution considered from the standpoint of population genetics.

Authors:  M Kimura
Journal:  Proc Natl Acad Sci U S A       Date:  1969-08       Impact factor: 11.205

10.  Theoretical foundations for a quantitative approach to paleogenetics. Part I: DNA.

Authors:  R Holmquist
Journal:  J Mol Evol       Date:  1971       Impact factor: 2.395

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  5 in total

1.  Nonuniformity of nucleotide substitution rates in molecular evolution: computer simulation and analysis of 5S ribosomal RNA sequences.

Authors:  C L Manske; D J Chapman
Journal:  J Mol Evol       Date:  1987       Impact factor: 2.395

2.  Simulation of protein evolution by random fixation of allowed codons.

Authors:  M Coates; S Stone
Journal:  J Mol Evol       Date:  1981       Impact factor: 2.395

3.  Accuracy of estimated phylogenetic trees from molecular data. I. Distantly related species.

Authors:  Y Tateno; M Nei; F Tajima
Journal:  J Mol Evol       Date:  1982       Impact factor: 2.395

4.  On investigating the statistical properties of the populous path algorithm by computer simulation. Counterconclusions to those of Tateno and Nei.

Authors:  J Czelusniak; M Goodman; G W Moore
Journal:  J Mol Evol       Date:  1978-05-12       Impact factor: 2.395

5.  What Fraction of Duplicates Observed in Recently Sequenced Genomes Is Segregating and Destined to Fail to Fix?

Authors:  Ashley I Teufel; Joanna Masel; David A Liberles
Journal:  Genome Biol Evol       Date:  2015-07-27       Impact factor: 3.416

  5 in total

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