Construction of Multilevel Structure for Avian Influenza Virus System Based on Granular Computing.

Exploring the genetic structure of influenza viruses attracts the attention in the field of molecular ecology and medical genetics, whose epidemics cause morbidity and mortality worldwide. The rapid variations in RNA strand and changes of protein structure of the virus result in low-accuracy subtypi...

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Published in:BioMed Research International Vol. 2017; pp. 1 - 8
Main Authors: Li, Yang, Liang, Qi-Hao, Sun, Meng-Meng, Tang, Xu-Qing, Zhu, Ping
Format: algorithm equations & formulas research tables/charts Journal Article
Published: Wiley-Blackwell 1/16/2017
Online Access:View this record in EBSCOhost
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      jtl: BioMed Research International
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      dt: 1/16/2017
      vid: 2017
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      pub: Wiley-Blackwell
      place: Malden, Massachusetts
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        10.1155/2017/5404180
        120749397
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        atl: Construction of Multilevel Structure for Avian Influenza Virus System Based on Granular Computing.
      aug:
        au:
          Li, Yang
          Liang, Qi-Hao
          Sun, Meng-Meng
          Tang, Xu-Qing
          Zhu, Ping
        affil: School of Science, Jiangnan University, Wuxi 214122, China
      sug:
        subj:
          Influenza A Virus
          Human
          Models, Structural
          Computing Methodologies
          Influenza, Avian Physiopathology
          RNA
          Proteins
          Genome
          Funding Source
      ab: Exploring the genetic structure of influenza viruses attracts the attention in the field of molecular ecology and medical genetics, whose epidemics cause morbidity and mortality worldwide. The rapid variations in RNA strand and changes of protein structure of the virus result in low-accuracy subtyping identification and make it difficult to develop effective drugs and vaccine. This paper constructs the evolutionary structure of avian influenza virus system considering both hemagglutinin and neuraminidase protein fragments. An optimization model was established to determine the rational granularity of the virus system for exploring the intrinsic relationship among the subtypes based on the fuzzy hierarchical evaluation index. Thus, an algorithm was presented to extract the rational structure. Furthermore, to reduce the systematic and computational complexity, the granular signatures of virus system were identified based on the coarse-grained idea and then its performance was evaluated through a designed classifier. The results showed that the obtained virus signatures could approximate and reflect the whole avian influenza virus system, indicating that the proposed method could identify the effective virus signatures. Once a new molecular virus is detected, it is efficient to identify the homologous virus hierarchically.
      pubtype: Academic Journal
      doctype:
        algorithm
        equations & formulas
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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