These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

135 related articles for article (PubMed ID: 35443027)

  • 1. MHCRoBERTa: pan-specific peptide-MHC class I binding prediction through transfer learning with label-agnostic protein sequences.
    Wang F; Wang H; Wang L; Lu H; Qiu S; Zang T; Zhang X; Hu Y
    Brief Bioinform; 2022 May; 23(3):. PubMed ID: 35443027
    [TBL] [Abstract][Full Text] [Related]  

  • 2. ACME: pan-specific peptide-MHC class I binding prediction through attention-based deep neural networks.
    Hu Y; Wang Z; Hu H; Wan F; Chen L; Xiong Y; Wang X; Zhao D; Huang W; Zeng J
    Bioinformatics; 2019 Dec; 35(23):4946-4954. PubMed ID: 31120490
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Deep learning pan-specific model for interpretable MHC-I peptide binding prediction with improved attention mechanism.
    Jin J; Liu Z; Nasiri A; Cui Y; Louis SY; Zhang A; Zhao Y; Hu J
    Proteins; 2021 Jul; 89(7):866-883. PubMed ID: 33594723
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Deep convolutional neural networks for pan-specific peptide-MHC class I binding prediction.
    Han Y; Kim D
    BMC Bioinformatics; 2017 Dec; 18(1):585. PubMed ID: 29281985
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Systematically benchmarking peptide-MHC binding predictors: From synthetic to naturally processed epitopes.
    Zhao W; Sher X
    PLoS Comput Biol; 2018 Nov; 14(11):e1006457. PubMed ID: 30408041
    [TBL] [Abstract][Full Text] [Related]  

  • 6. HLA class I binding prediction via convolutional neural networks.
    Vang YS; Xie X
    Bioinformatics; 2017 Sep; 33(17):2658-2665. PubMed ID: 28444127
    [TBL] [Abstract][Full Text] [Related]  

  • 7. High-Throughput MHC I Ligand Prediction Using MHCflurry.
    O'Donnell T; Rubinsteyn A
    Methods Mol Biol; 2020; 2120():113-127. PubMed ID: 32124315
    [TBL] [Abstract][Full Text] [Related]  

  • 8. MHCAttnNet: predicting MHC-peptide bindings for MHC alleles classes I and II using an attention-based deep neural model.
    Venkatesh G; Grover A; Srinivasaraghavan G; Rao S
    Bioinformatics; 2020 Jul; 36(Suppl_1):i399-i406. PubMed ID: 32657386
    [TBL] [Abstract][Full Text] [Related]  

  • 9. USMPep: universal sequence models for major histocompatibility complex binding affinity prediction.
    Vielhaben J; Wenzel M; Samek W; Strodthoff N
    BMC Bioinformatics; 2020 Jul; 21(1):279. PubMed ID: 32615972
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Precision Neoantigen Discovery Using Large-Scale Immunopeptidomes and Composite Modeling of MHC Peptide Presentation.
    Pyke RM; Mellacheruvu D; Dea S; Abbott C; Zhang SV; Phillips NA; Harris J; Bartha G; Desai S; McClory R; West J; Snyder MP; Chen R; Boyle SM
    Mol Cell Proteomics; 2023 Apr; 22(4):100506. PubMed ID: 36796642
    [TBL] [Abstract][Full Text] [Related]  

  • 11. DeepNetBim: deep learning model for predicting HLA-epitope interactions based on network analysis by harnessing binding and immunogenicity information.
    Yang X; Zhao L; Wei F; Li J
    BMC Bioinformatics; 2021 May; 22(1):231. PubMed ID: 33952199
    [TBL] [Abstract][Full Text] [Related]  

  • 12. MHCflurry: Open-Source Class I MHC Binding Affinity Prediction.
    O'Donnell TJ; Rubinsteyn A; Bonsack M; Riemer AB; Laserson U; Hammerbacher J
    Cell Syst; 2018 Jul; 7(1):129-132.e4. PubMed ID: 29960884
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Improved pan-specific MHC class I peptide-binding predictions using a novel representation of the MHC-binding cleft environment.
    Carrasco Pro S; Zimic M; Nielsen M
    Tissue Antigens; 2014 Feb; 83(2):94-100. PubMed ID: 24447175
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Predicting MHC-peptide binding affinity by differential boundary tree.
    Feng P; Zeng J; Ma J
    Bioinformatics; 2021 Jul; 37(Suppl_1):i254-i261. PubMed ID: 34252932
    [TBL] [Abstract][Full Text] [Related]  

  • 15. DeepLigand: accurate prediction of MHC class I ligands using peptide embedding.
    Zeng H; Gifford DK
    Bioinformatics; 2019 Jul; 35(14):i278-i283. PubMed ID: 31510651
    [TBL] [Abstract][Full Text] [Related]  

  • 16. DeepSeqPan, a novel deep convolutional neural network model for pan-specific class I HLA-peptide binding affinity prediction.
    Liu Z; Cui Y; Xiong Z; Nasiri A; Zhang A; Hu J
    Sci Rep; 2019 Jan; 9(1):794. PubMed ID: 30692623
    [TBL] [Abstract][Full Text] [Related]  

  • 17. NN-align. An artificial neural network-based alignment algorithm for MHC class II peptide binding prediction.
    Nielsen M; Lund O
    BMC Bioinformatics; 2009 Sep; 10():296. PubMed ID: 19765293
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Toward the prediction of class I and II mouse major histocompatibility complex-peptide-binding affinity: in silico bioinformatic step-by-step guide using quantitative structure-activity relationships.
    Hattotuwagama CK; Doytchinova IA; Flower DR
    Methods Mol Biol; 2007; 409():227-45. PubMed ID: 18450004
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Predicting MHC class I binder: existing approaches and a novel recurrent neural network solution.
    Jiang L; Yu H; Li J; Tang J; Guo Y; Guo F
    Brief Bioinform; 2021 Nov; 22(6):. PubMed ID: 34131696
    [TBL] [Abstract][Full Text] [Related]  

  • 20. IConMHC: a deep learning convolutional neural network model to predict peptide and MHC-I binding affinity.
    Pei B; Hsu YH
    Immunogenetics; 2020 Jul; 72(5):295-304. PubMed ID: 32577798
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 7.