163 related articles for article (PubMed ID: 38711371)
1. Predicting TCR sequences for unseen antigen epitopes using structural and sequence features.
Ji H; Wang XX; Zhang Q; Zhang C; Zhang HM
Brief Bioinform; 2024 Mar; 25(3):. PubMed ID: 38711371
[TBL] [Abstract][Full Text] [Related]
2. Predicting CD4 T-cell epitopes based on antigen cleavage, MHCII presentation, and TCR recognition.
Schneidman-Duhovny D; Khuri N; Dong GQ; Winter MB; Shifrut E; Friedman N; Craik CS; Pratt KP; Paz P; Aswad F; Sali A
PLoS One; 2018; 13(11):e0206654. PubMed ID: 30399156
[TBL] [Abstract][Full Text] [Related]
3. Current challenges for unseen-epitope TCR interaction prediction and a new perspective derived from image classification.
Moris P; De Pauw J; Postovskaya A; Gielis S; De Neuter N; Bittremieux W; Ogunjimi B; Laukens K; Meysman P
Brief Bioinform; 2021 Jul; 22(4):. PubMed ID: 33346826
[TBL] [Abstract][Full Text] [Related]
4. TPBTE: A model based on convolutional Transformer for predicting the binding of TCR to epitope.
Wu J; Qi M; Zhang F; Zheng Y
Mol Immunol; 2023 May; 157():30-41. PubMed ID: 36966551
[TBL] [Abstract][Full Text] [Related]
5. PiTE: TCR-epitope Binding Affinity Prediction Pipeline using Transformer-based Sequence Encoder.
Zhang P; Bang S; Lee H
Pac Symp Biocomput; 2023; 28():347-358. PubMed ID: 36540990
[TBL] [Abstract][Full Text] [Related]
6. An Attention Based Bidirectional LSTM Method to Predict the Binding of TCR and Epitope.
Bi J; Zheng Y; Wang C; Ding Y
IEEE/ACM Trans Comput Biol Bioinform; 2022; 19(6):3272-3280. PubMed ID: 34559661
[TBL] [Abstract][Full Text] [Related]
7. TITAN: T-cell receptor specificity prediction with bimodal attention networks.
Weber A; Born J; Rodriguez Martínez M
Bioinformatics; 2021 Jul; 37(Suppl_1):i237-i244. PubMed ID: 34252922
[TBL] [Abstract][Full Text] [Related]
8. Determining epitope specificity of T-cell receptors with transformers.
Khan AR; Reinders MJT; Khatri I
Bioinformatics; 2023 Nov; 39(11):. PubMed ID: 37847663
[TBL] [Abstract][Full Text] [Related]
9. Predicting recognition between T cell receptors and epitopes with TCRGP.
Jokinen E; Huuhtanen J; Mustjoki S; Heinonen M; Lähdesmäki H
PLoS Comput Biol; 2021 Mar; 17(3):e1008814. PubMed ID: 33764977
[TBL] [Abstract][Full Text] [Related]
10. Predicting TCR-Epitope Binding Specificity Using Deep Metric Learning and Multimodal Learning.
Luu AM; Leistico JR; Miller T; Kim S; Song JS
Genes (Basel); 2021 Apr; 12(4):. PubMed ID: 33920780
[TBL] [Abstract][Full Text] [Related]
11. TEINet: a deep learning framework for prediction of TCR-epitope binding specificity.
Jiang Y; Huo M; Cheng Li S
Brief Bioinform; 2023 Mar; 24(2):. PubMed ID: 36907658
[TBL] [Abstract][Full Text] [Related]
12. Quantifiable predictive features define epitope-specific T cell receptor repertoires.
Dash P; Fiore-Gartland AJ; Hertz T; Wang GC; Sharma S; Souquette A; Crawford JC; Clemens EB; Nguyen THO; Kedzierska K; La Gruta NL; Bradley P; Thomas PG
Nature; 2017 Jul; 547(7661):89-93. PubMed ID: 28636592
[TBL] [Abstract][Full Text] [Related]
13. ATM-TCR: TCR-Epitope Binding Affinity Prediction Using a Multi-Head Self-Attention Model.
Cai M; Bang S; Zhang P; Lee H
Front Immunol; 2022; 13():893247. PubMed ID: 35874725
[TBL] [Abstract][Full Text] [Related]
14. EPIC-TRACE: predicting TCR binding to unseen epitopes using attention and contextualized embeddings.
Korpela D; Jokinen E; Dumitrescu A; Huuhtanen J; Mustjoki S; Lähdesmäki H
Bioinformatics; 2023 Dec; 39(12):. PubMed ID: 38070156
[TBL] [Abstract][Full Text] [Related]
15. TULIP: A transformer-based unsupervised language model for interacting peptides and T cell receptors that generalizes to unseen epitopes.
Meynard-Piganeau B; Feinauer C; Weigt M; Walczak AM; Mora T
Proc Natl Acad Sci U S A; 2024 Jun; 121(24):e2316401121. PubMed ID: 38838016
[TBL] [Abstract][Full Text] [Related]
16. Identifying specificity groups in the T cell receptor repertoire.
Glanville J; Huang H; Nau A; Hatton O; Wagar LE; Rubelt F; Ji X; Han A; Krams SM; Pettus C; Haas N; Arlehamn CSL; Sette A; Boyd SD; Scriba TJ; Martinez OM; Davis MM
Nature; 2017 Jul; 547(7661):94-98. PubMed ID: 28636589
[TBL] [Abstract][Full Text] [Related]
17. The two-faced T cell epitope: examining the host-microbe interface with JanusMatrix.
Moise L; Gutierrez AH; Bailey-Kellogg C; Terry F; Leng Q; Abdel Hady KM; VerBerkmoes NC; Sztein MB; Losikoff PT; Martin WD; Rothman AL; De Groot AS
Hum Vaccin Immunother; 2013 Jul; 9(7):1577-86. PubMed ID: 23584251
[TBL] [Abstract][Full Text] [Related]
18. MITNet: a fusion transformer and convolutional neural network architecture approach for T-cell epitope prediction.
Darmawan JT; Leu JS; Avian C; Ratnasari NRP
Brief Bioinform; 2023 Jul; 24(4):. PubMed ID: 37253692
[TBL] [Abstract][Full Text] [Related]
19. Interpretable Prediction of SARS-CoV-2 Epitope-Specific TCR Recognition Using a Pre-Trained Protein Language Model.
Yoo S; Jeong M; Seomun S; Kim K; Han Y
IEEE/ACM Trans Comput Biol Bioinform; 2024; 21(3):428-438. PubMed ID: 38381638
[TBL] [Abstract][Full Text] [Related]
20. HeteroTCR: A heterogeneous graph neural network-based method for predicting peptide-TCR interaction.
Yu Z; Jiang M; Lan X
Commun Biol; 2024 Jun; 7(1):684. PubMed ID: 38834836
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]