Meta-iAVP: A Sequence-Based Meta-Predictor for Improving the Prediction of Antiviral Peptides Using Effective Feature Representation

Meta-iAVP: A Sequence-Based Meta-Predictor for Improving the Prediction of Antiviral Peptides Using Effective Feature Representation

In spite of the large-scale production and widespread distribution of vaccines and antiviral drugs, viruses remain a prominent human disease. Recently, the discovery of antiviral peptides (AVPs) has become an influential antiviral agent due to their extraordinary advantages. With the avalanche of ne...

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Bibliographic Details
Main Authors: Nalini Schaduangrat, Chanin Nantasenamat, Virapong Prachayasittikul, Watshara Shoombuatong
Format: Article
Language:English
Published: MDPI AG 2019-11-01
Series:International Journal of Molecular Sciences
Subjects:
therapeutic peptides
antiviral peptide
classification
machine learning
random forest
meta-predictor
Online Access:https://www.mdpi.com/1422-0067/20/22/5743

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