166 related articles for article (PubMed ID: 37147498)
21. Performance Evaluation of MHC Class-I Binding Prediction Tools Based on an Experimentally Validated MHC-Peptide Binding Data Set.
Bonsack M; Hoppe S; Winter J; Tichy D; Zeller C; Küpper MD; Schitter EC; Blatnik R; Riemer AB
Cancer Immunol Res; 2019 May; 7(5):719-736. PubMed ID: 30902818
[TBL] [Abstract][Full Text] [Related]
22. MultiRTA: a simple yet reliable method for predicting peptide binding affinities for multiple class II MHC allotypes.
Bordner AJ; Mittelmann HD
BMC Bioinformatics; 2010 Sep; 11():482. PubMed ID: 20868497
[TBL] [Abstract][Full Text] [Related]
23. Determination of a Predictive Cleavage Motif for Eluted Major Histocompatibility Complex Class II Ligands.
Paul S; Karosiene E; Dhanda SK; Jurtz V; Edwards L; Nielsen M; Sette A; Peters B
Front Immunol; 2018; 9():1795. PubMed ID: 30127785
[TBL] [Abstract][Full Text] [Related]
24. 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]
25. Structural prediction of peptides binding to MHC class I molecules.
Bui HH; Schiewe AJ; von Grafenstein H; Haworth IS
Proteins; 2006 Apr; 63(1):43-52. PubMed ID: 16447245
[TBL] [Abstract][Full Text] [Related]
26. 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]
27. Predicting peptide binding to Major Histocompatibility Complex molecules.
Liao WW; Arthur JW
Autoimmun Rev; 2011 Jun; 10(8):469-73. PubMed ID: 21333759
[TBL] [Abstract][Full Text] [Related]
28. Accurate pan-specific prediction of peptide-MHC class II binding affinity with improved binding core identification.
Andreatta M; Karosiene E; Rasmussen M; Stryhn A; Buus S; Nielsen M
Immunogenetics; 2015 Nov; 67(11-12):641-50. PubMed ID: 26416257
[TBL] [Abstract][Full Text] [Related]
29. Pan-Specific Prediction of Peptide-MHC Class I Complex Stability, a Correlate of T Cell Immunogenicity.
Rasmussen M; Fenoy E; Harndahl M; Kristensen AB; Nielsen IK; Nielsen M; Buus S
J Immunol; 2016 Aug; 197(4):1517-24. PubMed ID: 27402703
[TBL] [Abstract][Full Text] [Related]
30. Structure-aware deep model for MHC-II peptide binding affinity prediction.
Yu Y; Zu L; Jiang J; Wu Y; Wang Y; Xu M; Liu Q
BMC Genomics; 2024 Jan; 25(1):127. PubMed ID: 38291350
[TBL] [Abstract][Full Text] [Related]
31. Structural Prediction of Peptide-MHC Binding Modes.
Perez MAS; Cuendet MA; Röhrig UF; Michielin O; Zoete V
Methods Mol Biol; 2022; 2405():245-282. PubMed ID: 35298818
[TBL] [Abstract][Full Text] [Related]
32. Benchmarking predictions of MHC class I restricted T cell epitopes in a comprehensively studied model system.
Paul S; Croft NP; Purcell AW; Tscharke DC; Sette A; Nielsen M; Peters B
PLoS Comput Biol; 2020 May; 16(5):e1007757. PubMed ID: 32453790
[TBL] [Abstract][Full Text] [Related]
33. 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]
34. Predicting peptides that bind to MHC molecules using supervised learning of hidden Markov models.
Mamitsuka H
Proteins; 1998 Dec; 33(4):460-74. PubMed ID: 9849933
[TBL] [Abstract][Full Text] [Related]
35. Prediction of MHC class II-binding peptides using an evolutionary algorithm and artificial neural network.
Brusic V; Rudy G; Honeyman G; Hammer J; Harrison L
Bioinformatics; 1998; 14(2):121-30. PubMed ID: 9545443
[TBL] [Abstract][Full Text] [Related]
36. In silico design of MHC class I high binding affinity peptides through motifs activation map.
Xiao Z; Zhang Y; Yu R; Chen Y; Jiang X; Wang Z; Li S
BMC Bioinformatics; 2018 Dec; 19(Suppl 19):516. PubMed ID: 30598069
[TBL] [Abstract][Full Text] [Related]
37. 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]
38. Improved prediction of MHC class I and class II epitopes using a novel Gibbs sampling approach.
Nielsen M; Lundegaard C; Worning P; Hvid CS; Lamberth K; Buus S; Brunak S; Lund O
Bioinformatics; 2004 Jun; 20(9):1388-97. PubMed ID: 14962912
[TBL] [Abstract][Full Text] [Related]
39. 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]
40. Ranking-Based Convolutional Neural Network Models for Peptide-MHC Class I Binding Prediction.
Chen Z; Min MR; Ning X
Front Mol Biosci; 2021; 8():634836. PubMed ID: 34079815
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]