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BioMed Research International
Volume 2017, Article ID 5404180, 7 pages
Research Article

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

School of Science, Jiangnan University, Wuxi 214122, China

Correspondence should be addressed to Ping Zhu; nc.ude.nangnaij@gnipuhz

Received 11 September 2016; Revised 1 December 2016; Accepted 14 December 2016; Published 16 January 2017

Academic Editor: Hao-Teng Chang

Copyright © 2017 Yang Li et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


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.