131 related articles for article (PubMed ID: 15542371)
21. A systematic approach for comprehensive T-cell epitope discovery using peptide libraries.
Beissbarth T; Tye-Din JA; Smyth GK; Speed TP; Anderson RP
Bioinformatics; 2005 Jun; 21 Suppl 1():i29-37. PubMed ID: 15961469
[TBL] [Abstract][Full Text] [Related]
22. Synthesis and biological evaluation of two chemically modified peptide epitopes for the class I MHC protein HLA-B*2705.
Jones MA; Hislop AD; Snaith JS
Org Biomol Chem; 2006 Oct; 4(20):3769-77. PubMed ID: 17024283
[TBL] [Abstract][Full Text] [Related]
23. Predicting peptides bound to I-Ag7 class II histocompatibility molecules using a novel expectation-maximization alignment algorithm.
Chang KY; Suri A; Unanue ER
Proteomics; 2007 Feb; 7(3):367-77. PubMed ID: 17211830
[TBL] [Abstract][Full Text] [Related]
24. A computational resource for the prediction of peptide binding to Indian rhesus macaque MHC class I molecules.
Peters B; Bui HH; Sidney J; Weng Z; Loffredo JT; Watkins DI; Mothé BR; Sette A
Vaccine; 2005 Nov; 23(45):5212-24. PubMed ID: 16137805
[TBL] [Abstract][Full Text] [Related]
25. Fab antibodies capable of blocking T cells by competitive binding have the identical specificity but a higher affinity to the MHC-peptide-complex than the T cell receptor.
Neumann F; Sturm C; Hülsmeyer M; Dauth N; Guillaume P; Luescher IF; Pfreundschuh M; Held G
Immunol Lett; 2009 Aug; 125(2):86-92. PubMed ID: 19524620
[TBL] [Abstract][Full Text] [Related]
26. Prediction of peptide structure: how far are we?
Thomas A; Deshayes S; Decaffmeyer M; Van Eyck MH; Charloteaux B; Brasseur R
Proteins; 2006 Dec; 65(4):889-97. PubMed ID: 17019719
[TBL] [Abstract][Full Text] [Related]
27. ProPred analysis and experimental evaluation of promiscuous T-cell epitopes of three major secreted antigens of Mycobacterium tuberculosis.
Mustafa AS; Shaban FA
Tuberculosis (Edinb); 2006 Mar; 86(2):115-24. PubMed ID: 16039905
[TBL] [Abstract][Full Text] [Related]
28. New horizons in mouse immunoinformatics: reliable in silico prediction of mouse class I histocompatibility major complex peptide binding affinity.
Hattotuwagama CK; Guan P; Doytchinova IA; Flower DR
Org Biomol Chem; 2004 Nov; 2(22):3274-83. PubMed ID: 15534705
[TBL] [Abstract][Full Text] [Related]
29. The wide diversity and complexity of peptides bound to class II MHC molecules.
Suri A; Lovitch SB; Unanue ER
Curr Opin Immunol; 2006 Feb; 18(1):70-7. PubMed ID: 16316750
[TBL] [Abstract][Full Text] [Related]
30. In silico prediction of peptide binding affinity to class I mouse major histocompatibility complexes: a comparative molecular similarity index analysis (CoMSIA) study.
Hattotuwagama CK; Doytchinova IA; Flower DR
J Chem Inf Model; 2005; 45(5):1415-23. PubMed ID: 16180918
[TBL] [Abstract][Full Text] [Related]
31. T-cell epitopes of the La/SSB autoantigen: prediction based on the homology modeling of HLA-DQ2/DQ7 with the insulin-B peptide/HLA-DQ8 complex.
Kosmopoulou A; Vlassi M; Stavrakoudis A; Sakarellos C; Sakarellos-Daitsiotis M
J Comput Chem; 2006 Jul; 27(9):1033-44. PubMed ID: 16639700
[TBL] [Abstract][Full Text] [Related]
32. Prediction of T-cell epitopes using biosupport vector machines.
Yang ZR; Johnson FC
J Chem Inf Model; 2005; 45(5):1424-8. PubMed ID: 16180919
[TBL] [Abstract][Full Text] [Related]
33. Predicting class I major histocompatibility complex (MHC) binders using multivariate statistics: comparison of discriminant analysis and multiple linear regression.
Doytchinova IA; Flower DR
J Chem Inf Model; 2007; 47(1):234-8. PubMed ID: 17238269
[TBL] [Abstract][Full Text] [Related]
34. Quantitative structure-activity relationships and the prediction of MHC supermotifs.
Doytchinova IA; Guan P; Flower DR
Methods; 2004 Dec; 34(4):444-53. PubMed ID: 15542370
[TBL] [Abstract][Full Text] [Related]
35. In silico quantitative prediction of peptides binding affinity to human MHC molecule: an intuitive quantitative structure-activity relationship approach.
Tian F; Yang L; Lv F; Yang Q; Zhou P
Amino Acids; 2009 Mar; 36(3):535-54. PubMed ID: 18575802
[TBL] [Abstract][Full Text] [Related]
36. Class II HLA-peptide binding prediction using structural principles.
Mohanapriya A; Lulu S; Kayathri R; Kangueane P
Hum Immunol; 2009 Mar; 70(3):159-69. PubMed ID: 19187794
[TBL] [Abstract][Full Text] [Related]
37. Presentation assessment of minor histocompatibility antigens by predictive proteasomal cleavage analysis.
Khattab B; Eiz-Vesper B; Ganser A; Hertenstein B; Blasczyk R
Ann Hematol; 2004 Feb; 83(2):107-13. PubMed ID: 14648025
[TBL] [Abstract][Full Text] [Related]
38. Crystal structures of murine MHC Class I H-2 D(b) and K(b) molecules in complex with CTL epitopes from influenza A virus: implications for TCR repertoire selection and immunodominance.
Meijers R; Lai CC; Yang Y; Liu JH; Zhong W; Wang JH; Reinherz EL
J Mol Biol; 2005 Feb; 345(5):1099-110. PubMed ID: 15644207
[TBL] [Abstract][Full Text] [Related]
39. 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]
40. Definition of MHC supertypes through clustering of MHC peptide-binding repertoires.
Reche PA; Reinherz EL
Methods Mol Biol; 2007; 409():163-73. PubMed ID: 18449999
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]
