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Published on in Vol 3, No 1 (2022): Jan-Dec

Preprints (earlier versions) of this paper are available at https://www.biorxiv.org/content/10.1101/2021.03.19.435772v1, first published .
Prediction of Antibody-Antigen Binding via Machine Learning: Development of Data Sets and Evaluation of Methods

Prediction of Antibody-Antigen Binding via Machine Learning: Development of Data Sets and Evaluation of Methods

Prediction of Antibody-Antigen Binding via Machine Learning: Development of Data Sets and Evaluation of Methods

Authors of this article:

Chao Ye1 Author Orcid Image ;   Wenxing Hu2 Author Orcid Image ;   Bruno Gaeta1 Author Orcid Image

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  1. Li D, Pucci F, Rooman M. Prediction of Paratope–Epitope Pairs Using Convolutional Neural Networks. International Journal of Molecular Sciences 2024;25(10):5434 View
  2. Ahmed F, Aly S, Liu X. NABP-BERT: NANOBODY®-antigen binding prediction based on bidirectional encoder representations from transformers (BERT) architecture. Briefings in Bioinformatics 2024;26(1) View
  3. Ahmed F, Aly S, El-Tabakh M, Liu X. NABP-LSTM-Att: Nanobody–Antigen binding prediction using bidirectional LSTM and soft attention mechanism. Computational Biology and Chemistry 2025;118:108490 View
  4. Sun C, Li X, Xu H, Tang Y, Bai G, Wang Y, Ma B. SAGERank: inductive learning of protein–protein interaction from antibody–antigen recognition. Chemical Science 2025;16(38):17885 View

Books/Policy Documents

  1. Sardar U, Ali S, Ayub M, Shoaib M, Bashir K, Khan I, Patterson M. Bioinformatics Research and Applications. View
  2. Iliyas I, Isa A, Kile S, Shanga N. Artificial Intelligence in Precision Drug Design, Volume 2. View