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Global informatics and physical property selection in protein sequences.
Scheraga, Harold A; Rackovsky, S.
Afiliação
  • Scheraga HA; Department of Chemistry and Chemical Biology, Baker Laboratory, Cornell University, Ithaca, NY 14853; has5@cornell.edu srr87@cornell.edu.
  • Rackovsky S; Department of Chemistry and Chemical Biology, Baker Laboratory, Cornell University, Ithaca, NY 14853; Department of Pharmacology and Systems Therapeutics, Icahn School of Medicine at Mount Sinai, New York, NY 10029 has5@cornell.edu srr87@cornell.edu.
Proc Natl Acad Sci U S A ; 113(7): 1808-10, 2016 Feb 16.
Article em En | MEDLINE | ID: mdl-26831093
ABSTRACT
The degree of informatic independence between the physical properties of amino acids as encoded in actual protein sequences is calculated. It is shown that no physical property can be identified that carries significantly less information than others and that the information overlap between different properties and different length scales along the sequence is essentially zero. These observations suggest that bioinformatic models based on arbitrarily selected sets of physical properties are inherently deficient.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Proteínas / Biologia Computacional Idioma: En Revista: Proc Natl Acad Sci U S A Ano de publicação: 2016 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Proteínas / Biologia Computacional Idioma: En Revista: Proc Natl Acad Sci U S A Ano de publicação: 2016 Tipo de documento: Article