| 1 |
Critical review of conformational B-cell epitope prediction methods.BRIEFINGS IN BIOINFORMATICS 2022. pdf |
| 2 |
CRESSP: a comprehensive pipeline for prediction of immunopathogenic SARS-CoV-2 epitopes using structural properties of proteins. BRIEFINGS IN BIOINFORMATICS 2022. pdf |
| 3 |
epitope3D: a machine learning method for conformational B-cell epitope prediction .BRIEFINGS IN BIOINFORMATICS 2022. pdf |
| 4 |
NetBCE: An Interpretable Deep Neural Network for Accurate Prediction of Linear B-cell Epitopes.GENOMICS PROTEOMICS & BIOINFORMATICS. 2022 |
| 5 |
BepiPred-3.0: Improved B-cell epitope prediction using protein language models. PROTEIN SCIENCE. 2022 |
| 6 |
SEMA: Antigen B-cell conformational epitope prediction using deep transfer learning. FRONTIERS IN IMMUNOLOGY.2022 |
| 7 |
ATM-TCR: TCR-Epitope Binding Affinity Prediction Using a Multi-Head Self-Attention Model. FRONTIERS IN IMMUNOLOGY.2022 |
| 8 |
EpiDope: a deep neural network for linear B-cell epitope prediction. 2021 |
| 9 |
In silico T cell epitope identification for SARS-CoV-2: Progress and perspectives. ADVANCED DRUG DELIVERY REVIEWS.2021 |
| 10 |
NetTCR-2.1: Lessons and guidance on how to develop models for TCR specificity predictions FRONTIERS IN IMMUNOLOGY. 2022 |
| 11 |
DLpTCR: an ensemble deep learning framework for predicting immunogenic peptide recognized by T cell receptor.
. BRIEFINGS IN BIOINFORMATICS. 2021 |
| 12 |
Attention-aware contrastive learning for predicting T cell receptor-antigen binding specificity. BRIEFINGS IN BIOINFORMATICS 2022. pdf |
| 13 |
TITAN: T-cell receptor specificity prediction with bimodal attention networks. BIOINFORMATICS.2021 |
| 14 |
T Cell Epitope Predictions. ANNUAL REVIEW OF IMMUNOLOGY..2020 |
| 15 |
Methods for sequence and structural analysis of B and T cell receptor repertoires. COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL. 2020 |
| 16 |
LBCEPred: a machine learning model to predict linear B-cell epitopes. BRIEFINGS IN BIOINFORMATICS. 2022 |
| |
|
| |
|
| |
|
| |
|
| |
|
| |
|