BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

179 related articles for article (PubMed ID: 23754940)

  • 1. Scrutinizing MHC-I binding peptides and their limits of variation.
    Koch CP; Perna AM; Pillong M; Todoroff NK; Wrede P; Folkers G; Hiss JA; Schneider G
    PLoS Comput Biol; 2013; 9(6):e1003088. PubMed ID: 23754940
    [TBL] [Abstract][Full Text] [Related]  

  • 2. 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]  

  • 3. Prediction of MHC class I binding peptides, using SVMHC.
    Dönnes P; Elofsson A
    BMC Bioinformatics; 2002 Sep; 3():25. PubMed ID: 12225620
    [TBL] [Abstract][Full Text] [Related]  

  • 4. In silico prediction of peptide-MHC binding affinity using SVRMHC.
    Liu W; Wan J; Meng X; Flower DR; Li T
    Methods Mol Biol; 2007; 409():283-91. PubMed ID: 18450008
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Prediction of MHC class I binding peptides using profile motifs.
    Reche PA; Glutting JP; Reinherz EL
    Hum Immunol; 2002 Sep; 63(9):701-9. PubMed ID: 12175724
    [TBL] [Abstract][Full Text] [Related]  

  • 6. 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]  

  • 7. Poor correspondence between predicted and experimental binding of peptides to class I MHC molecules.
    Andersen MH; Tan L; Søndergaard I; Zeuthen J; Elliott T; Haurum JS
    Tissue Antigens; 2000 Jun; 55(6):519-31. PubMed ID: 10902608
    [TBL] [Abstract][Full Text] [Related]  

  • 8. 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]  

  • 9. TAPPred prediction of TAP-binding peptides in antigens.
    Bhasin M; Lata S; Raghava GP
    Methods Mol Biol; 2007; 409():381-6. PubMed ID: 18450016
    [TBL] [Abstract][Full Text] [Related]  

  • 10. POPI: predicting immunogenicity of MHC class I binding peptides by mining informative physicochemical properties.
    Tung CW; Ho SY
    Bioinformatics; 2007 Apr; 23(8):942-9. PubMed ID: 17384427
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Designing High Binding Affinity Peptides for MHC Class I Using MAM: An In Silico Approach.
    Zhang YW
    Methods Mol Biol; 2024; 2809():263-274. PubMed ID: 38907903
    [TBL] [Abstract][Full Text] [Related]  

  • 12. PromPDD, a web-based tool for the prediction, deciphering and design of promiscuous peptides that bind to HLA class I molecules.
    Zhang S; Chen J; Hong P; Li J; Tian Y; Wu Y; Wang S
    J Immunol Methods; 2020 Jan; 476():112685. PubMed ID: 31678214
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Improved prediction of MHC class I binders/non-binders peptides through artificial neural network using variable learning rate: SARS corona virus, a case study.
    Soam SS; Bhasker B; Mishra BN
    Adv Exp Med Biol; 2011; 696():223-9. PubMed ID: 21431562
    [TBL] [Abstract][Full Text] [Related]  

  • 14. A comprehensive review and performance evaluation of bioinformatics tools for HLA class I peptide-binding prediction.
    Mei S; Li F; Leier A; Marquez-Lago TT; Giam K; Croft NP; Akutsu T; Smith AI; Li J; Rossjohn J; Purcell AW; Song J
    Brief Bioinform; 2020 Jul; 21(4):1119-1135. PubMed ID: 31204427
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Methods for prediction of peptide binding to MHC molecules: a comparative study.
    Yu K; Petrovsky N; Schönbach C; Koh JY; Brusic V
    Mol Med; 2002 Mar; 8(3):137-48. PubMed ID: 12142545
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Design of enhanced agonists through the use of a new virtual screening method: application to peptides that bind class I major histocompatibility complex (MHC) molecules.
    Madurga S; Belda I; Llorà X; Giralt E
    Protein Sci; 2005 Aug; 14(8):2069-79. PubMed ID: 16046628
    [TBL] [Abstract][Full Text] [Related]  

  • 17. MHC-I prediction using a combination of T cell epitopes and MHC-I binding peptides.
    Vider-Shalit T; Louzoun Y
    J Immunol Methods; 2011 Nov; 374(1-2):43-6. PubMed ID: 20920507
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Prediction of peptides binding to MHC class I and II alleles by temporal motif mining.
    Meydan C; Otu HH; Sezerman OU
    BMC Bioinformatics; 2013; 14 Suppl 2(Suppl 2):S13. PubMed ID: 23368521
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Gapped sequence alignment using artificial neural networks: application to the MHC class I system.
    Andreatta M; Nielsen M
    Bioinformatics; 2016 Feb; 32(4):511-7. PubMed ID: 26515819
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Improving the prediction of HLA class I-binding peptides using a supertype-based method.
    Wang S; Bai Z; Han J; Tian Y; Shang X; Wang L; Li J; Wu Y
    J Immunol Methods; 2014 Mar; 405():109-20. PubMed ID: 24508661
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 9.