Source:http://linkedlifedata.com/resource/pubmed/id/15958784
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rdf:type | |
lifeskim:mentions | |
pubmed:issue |
10
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pubmed:dateCreated |
2005-9-9
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pubmed:abstractText |
It has been suggested that volatility, the proportion of mutations which change an amino acid, can be used to infer the level of natural selection acting upon a gene. This conjecture is supported by a correlation between volatility and the rate of nonsynonymous substitution (dN), or the ratio of nonsynonymous and synonymous substitution rates, in a variety of organisms. These organisms include yeast, in which the correlations are quite strong. Here we show that these correlations are a by-product of a correlation between synonymous codon bias toward translationally optimal codons and dN. Although this analysis suggests that volatility is not a good measure of the selection, we suggest that it might be possible to infer something about the level of natural selection, from a single genome sequence, using translational codon bias.
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pubmed:language |
eng
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pubmed:journal | |
pubmed:citationSubset |
IM
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pubmed:chemical | |
pubmed:status |
MEDLINE
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pubmed:month |
Oct
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pubmed:issn |
0737-4038
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pubmed:author | |
pubmed:issnType |
Print
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pubmed:volume |
22
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pubmed:owner |
NLM
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pubmed:authorsComplete |
Y
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pubmed:pagination |
2022-6
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pubmed:dateRevised |
2009-11-19
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pubmed:meshHeading |
pubmed-meshheading:15958784-Base Sequence,
pubmed-meshheading:15958784-Codon,
pubmed-meshheading:15958784-Evolution, Molecular,
pubmed-meshheading:15958784-Genes, Fungal,
pubmed-meshheading:15958784-Protein Biosynthesis,
pubmed-meshheading:15958784-Saccharomyces,
pubmed-meshheading:15958784-Saccharomyces cerevisiae,
pubmed-meshheading:15958784-Selection, Genetic,
pubmed-meshheading:15958784-Sequence Alignment,
pubmed-meshheading:15958784-Statistics, Nonparametric
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pubmed:year |
2005
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pubmed:articleTitle |
A dissection of volatility in yeast.
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pubmed:affiliation |
Section of Evolutionary Biology, Department Biology II, Ludwig-Maximilians-University Munich, Planegg-Martinsried, Germany. stoletzki@zi.biologie.uni-muenchen.de
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pubmed:publicationType |
Journal Article
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