Title
Computational identification of physicochemical signatures for host tropism of influenza A virus.
Abstract
Avian influenza viruses from migratory birds have managed to cross host species barriers and infected various hosts like human and swine. Epidemics and pandemics might occur when influenza viruses are adapted to humans, causing deaths and enormous economic loss. Receptor-binding specificity of the virus is one of the key factors for the transmission of influenza viruses across species. The determination of host tropism and understanding of molecular properties would help identify the mechanism why zoonotic influenza viruses can cross species barrier and infect humans. In this study, we have constructed computational models for host tropism prediction on human-adapted subtypes of influenza HA proteins using random forest. The feature vectors of the prediction models were generated based on seven physicochemical properties of amino acids from influenza sequences of three major hosts. Feature aggregation and associative rules were further applied to select top 20 features and extract host-associated physicochemical signatures on the combined model of nonspecific subtypes. The prediction model achieved high performance (Accuracy = 0.948 , Precision = 0.954 , MCC = 0.922 ). Support and confidence rates were calculated for the host class-association rules. The results indicated that secondary structure and normalized Van der Waals volume were identified as more important physicochemical signatures in determining the host tropism.
Year
DOI
Venue
2018
10.1142/S0219720018400231
JOURNAL OF BIOINFORMATICS AND COMPUTATIONAL BIOLOGY
Keywords
Field
DocType
Influenza,hemagglutinin,host tropism,physicochemical signature,association rules
Virus,Biology,Hemagglutinin (influenza),Influenza A virus subtype H5N1,Host tropism,Bioinformatics,Computational biology,Pandemic,Feature aggregation,Influenza A virus
Journal
Volume
Issue
ISSN
16
SP6
0219-7200
Citations 
PageRank 
References 
1
0.43
7
Authors
4
Name
Order
Citations
PageRank
Rui Yin112.80
Xinrui Zhou212.12
Jie Zheng312115.85
C K Kwoh4517.09