Title:Using Amino Acid Factor Scores to Predict Avian-to-Human Transmission of Avian Influenza Viruses: A Machine Learning Study
Volume: 20
Issue: 10
Author(s): Jia Wang, Zheng Kou, Mojie Duan, Chuang Ma and Yanhong Zhou
Affiliation:
Keywords:
AAIndex, amino acid factor, avian influenza A virus, decision tree, interspecies transmission, machine learning,
naive bayes, random forest, support vector machine.
Abstract: In this study, the problem of predicting interspecies transmission of avian influenza viruses (AIVs) was investigated
with machine learning methods. We identified 87 signature positions in AIV protein sequences with information entropy
method and encoded these positions with five amino acid factor scores (AAFactors) concentrated from 491 physicochemical
and biochemical properties of amino acids. We constructed four prediction models by integrating these five features
with commonly used machine learning technologies including Decision Tree, Naive Bayes, Random Forest and
Support Vector Machine. The cross validation experiment results demonstrated the power of AAFactors in predicting
avian-to-human transmission of AIVs. Comparative analysis revealed the strengths and weaknesses of different machine
learning methods, and the importance of different AAFactors to the prediction.
