Dataset Information

AI4AVP: an antiviral peptides predictor in deep learning approach with generative adversarial network data augmentation.

ABSTRACT:

Motivation

Antiviral peptides (AVPs) from various sources suggest the possibility of developing peptide drugs for treating viral diseases. Because of the increasing number of identified AVPs and the advances in deep learning theory, it is reasonable to experiment with peptide drug design using in silico methods.

Results

We collected the most up-to-date AVPs and used deep learning to construct a sequence-based binary classifier. A generative adversarial network was employed to augment the number of AVPs in the positive training dataset and enable our deep learning convolutional neural network (CNN) model to learn from the negative dataset. Our classifier outperformed other state-of-the-art classifiers when using the testing dataset. We have placed the trained classifiers on a user-friendly web server, AI4AVP, for the research community.

Availability and implementation

AI4AVP is freely accessible at http://axp.iis.sinica.edu.tw/AI4AVP/; codes and datasets for the peptide GAN and the AVP predictor CNN are available at https://github.com/lsbnb/amp_gan and https://github.com/LinTzuTang/AI4AVP_predictor.

Supplementary information

Supplementary data are available at Bioinformatics Advances online.

SUBMITTER: Lin TT

PROVIDER: S-EPMC9710571 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

AI4AVP: an antiviral peptides predictor in deep learning approach with generative adversarial network data augmentation.

Lin Tzu-Tang TT Sun Yih-Yun YY Wang Ching-Tien CT Cheng Wen-Chih WC Lu I-Hsuan IH Lin Chung-Yen CY Chen Shu-Hwa SH

Bioinformatics advances 20221026 1

<h4>Motivation</h4>Antiviral peptides (AVPs) from various sources suggest the possibility of developing peptide drugs for treating viral diseases. Because of the increasing number of identified AVPs and the advances in deep learning theory, it is reasonable to experiment with peptide drug design using <i>in silico</i> methods.<h4>Results</h4>We collected the most up-to-date AVPs and used deep learning to construct a sequence-based binary classifier. A generative adversarial network was employed ...[more]

PMID: 36699402

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Dataset Information

AI4AVP: an antiviral peptides predictor in deep learning approach with generative adversarial network data augmentation.

Motivation

Results

Availability and implementation

Supplementary information

Publications

AI4AVP: an antiviral peptides predictor in deep learning approach with generative adversarial network data augmentation.

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