Predicting interspecies transmission of avian influenza virus based on wavelet packet decomposition.

Abstract:

:Using wavelet packet decomposition, the energy coefficients in the fifth level of viral protein sequences were achieved to predict interspecies transmission. Since avian-origin influenza viruses could have high sequence similarities with human-origin avian influenza virus and could have the phenotype of interspecies transmission, viral data should be filtered to prevent the misconduct of feature selection and false performance of predicting models. Considering the balance of data size, the empirical cut-off value 97% was used to screen avian-origin influenza virus with high sequence similarity. The excellent performances of cross validation show that the SVM model has the best capability of predicting transmission and evaluating the contribution of five amino acid factors. The robust model was finally used to evaluate the filtered data of avian-origin virus and the results confirmed that double check for ambiguous phenotype of avian-origin virus with high sequence similarity was necessary and part of them have the ability to across species barriers.

journal_name

Comput Biol Chem

authors

Qiang X,Kou Z

doi

10.1016/j.compbiolchem.2018.11.029

subject

Has Abstract

pub_date

2019-02-01 00:00:00

pages

455-459

eissn

1476-9271

issn

1476-928X

pii

S1476-9271(18)30793-X

journal_volume

78

pub_type

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