Novel Numerical Characterization of Protein Sequences Based on Individual Amino Acid and Its Application.

The hydrophobicity and hydrophilicity of amino acids play a very important role in protein folding and its interaction with the environment and other molecules, as well as its catalytic mechanism. Based on the two physicochemical indexes, a 2D graphical representation of protein sequences is introdu...

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Publicado en:BioMed Research International Vol. 2015; pp. 1 - 9
Autores principales: Zhang, Yan-ping, Sheng, Ya-jun, Zheng, Wei, He, Ping-an, Ruan, Ji-shuo
Formato: equations & formulas research tables/charts Journal Article
Publicado: Wiley-Blackwell 2/2/2015
Acceso en línea:Ver este registro en EBSCOhost
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      dt: 2/2/2015
      vid: 2015
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      pub: Wiley-Blackwell
      place: Malden, Massachusetts
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        10.1155/2015/909567
        109273315
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        atl: Novel Numerical Characterization of Protein Sequences Based on Individual Amino Acid and Its Application.
      aug:
        au:
          Zhang, Yan-ping
          Sheng, Ya-jun
          Zheng, Wei
          He, Ping-an
          Ruan, Ji-shuo
        affil: Department of Mathematics, School of Science, Hebei University of Engineering, Handan 056038, China
      sug:
        subj:
          Amino Acids
          Proteins Physiology
          Diffusion of Innovation
          DNA Physiology
          Biometrics
          Human
          Statistics
          Funding Source
      ab: The hydrophobicity and hydrophilicity of amino acids play a very important role in protein folding and its interaction with the environment and other molecules, as well as its catalytic mechanism. Based on the two physicochemical indexes, a 2D graphical representation of protein sequences is introduced; meanwhile, a new numerical characteristic has been proposed to compute the distance of different sequences for analysis of sequence similarity/dissimilarity on the basis of this graphical representation. Furthermore, we apply the new distance in the similarities/dissimilarities of ND5 proteins of nine species and predict the four major classes based on the dataset containing 639 domains. The results show that the method is simple and effective.
      pubtype: Academic Journal
      doctype:
        equations & formulas
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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