192 related articles for article (PubMed ID: 18450006)
41. Enhancing in silico protein-based vaccine discovery for eukaryotic pathogens using predicted peptide-MHC binding and peptide conservation scores.
Goodswen SJ; Kennedy PJ; Ellis JT
PLoS One; 2014; 9(12):e115745. PubMed ID: 25545691
[TBL] [Abstract][Full Text] [Related]
42. PepDist: a new framework for protein-peptide binding prediction based on learning peptide distance functions.
Hertz T; Yanover C
BMC Bioinformatics; 2006 Mar; 7 Suppl 1(Suppl 1):S3. PubMed ID: 16723006
[TBL] [Abstract][Full Text] [Related]
43. Prediction of promiscuous and high-affinity mutated MHC binders.
Bhasin M; Raghava GP
Hybrid Hybridomics; 2003 Aug; 22(4):229-34. PubMed ID: 14511568
[TBL] [Abstract][Full Text] [Related]
44. 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]
45. 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]
46. 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]
47. MHC-NP: predicting peptides naturally processed by the MHC.
Giguère S; Drouin A; Lacoste A; Marchand M; Corbeil J; Laviolette F
J Immunol Methods; 2013 Dec; 400-401():30-6. PubMed ID: 24144535
[TBL] [Abstract][Full Text] [Related]
48. A geometric and algebraic view of MHC-peptide complexes and their binding properties.
Cano P; Fan B
BMC Struct Biol; 2001; 1():2. PubMed ID: 11472639
[TBL] [Abstract][Full Text] [Related]
49. NetMHC-3.0: accurate web accessible predictions of human, mouse and monkey MHC class I affinities for peptides of length 8-11.
Lundegaard C; Lamberth K; Harndahl M; Buus S; Lund O; Nielsen M
Nucleic Acids Res; 2008 Jul; 36(Web Server issue):W509-12. PubMed ID: 18463140
[TBL] [Abstract][Full Text] [Related]
50. Building a meta-predictor for MHC class II-binding peptides.
Huang L; Karpenko O; Murugan N; Dai Y
Methods Mol Biol; 2007; 409():355-64. PubMed ID: 18450014
[TBL] [Abstract][Full Text] [Related]
51. The PickPocket method for predicting binding specificities for receptors based on receptor pocket similarities: application to MHC-peptide binding.
Zhang H; Lund O; Nielsen M
Bioinformatics; 2009 May; 25(10):1293-9. PubMed ID: 19297351
[TBL] [Abstract][Full Text] [Related]
52. Quantification of Uncertainty in Peptide-MHC Binding Prediction Improves High-Affinity Peptide Selection for Therapeutic Design.
Zeng H; Gifford DK
Cell Syst; 2019 Aug; 9(2):159-166.e3. PubMed ID: 31176619
[TBL] [Abstract][Full Text] [Related]
53. Predicting the binding affinity of MHC class II peptides.
Altiparmak F; Akalin A; Ferhatosmanoglu H
Comput Syst Bioinformatics Conf; 2006; ():331-4. PubMed ID: 17369651
[TBL] [Abstract][Full Text] [Related]
54. Predicting sequences and structures of MHC-binding peptides: a computational combinatorial approach.
Zen J; Treutlein HR; Rudy GB
J Comput Aided Mol Des; 2001 Jun; 15(6):573-86. PubMed ID: 11495228
[TBL] [Abstract][Full Text] [Related]
55. A community resource benchmarking predictions of peptide binding to MHC-I molecules.
Peters B; Bui HH; Frankild S; Nielson M; Lundegaard C; Kostem E; Basch D; Lamberth K; Harndahl M; Fleri W; Wilson SS; Sidney J; Lund O; Buus S; Sette A
PLoS Comput Biol; 2006 Jun; 2(6):e65. PubMed ID: 16789818
[TBL] [Abstract][Full Text] [Related]
56. Prediction of supertype-specific HLA class I binding peptides using support vector machines.
Zhang GL; Bozic I; Kwoh CK; August JT; Brusic V
J Immunol Methods; 2007 Mar; 320(1-2):143-54. PubMed ID: 17303158
[TBL] [Abstract][Full Text] [Related]
57. 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]
58. 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]
59. 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]
60. Prediction of MHC-peptide binding: a systematic and comprehensive overview.
Lafuente EM; Reche PA
Curr Pharm Des; 2009; 15(28):3209-20. PubMed ID: 19860671
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]