217 related articles for article (PubMed ID: 17059589)
1. SVRMHC prediction server for MHC-binding peptides.
Wan J; Liu W; Xu Q; Ren Y; Flower DR; Li T
BMC Bioinformatics; 2006 Oct; 7():463. PubMed ID: 17059589
[TBL] [Abstract][Full Text] [Related]
2. Quantitative prediction of mouse class I MHC peptide binding affinity using support vector machine regression (SVR) models.
Liu W; Meng X; Xu Q; Flower DR; Li T
BMC Bioinformatics; 2006 Mar; 7():182. PubMed ID: 16579851
[TBL] [Abstract][Full Text] [Related]
3. 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]
4. 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]
5. Prediction of MHC class II binding affinity using SMM-align, a novel stabilization matrix alignment method.
Nielsen M; Lundegaard C; Lund O
BMC Bioinformatics; 2007 Jul; 8():238. PubMed ID: 17608956
[TBL] [Abstract][Full Text] [Related]
6. MHCPred: bringing a quantitative dimension to the online prediction of MHC binding.
Guan P; Doytchinova IA; Zygouri C; Flower DR
Appl Bioinformatics; 2003; 2(1):63-6. PubMed ID: 15130834
[TBL] [Abstract][Full Text] [Related]
7. Major histocompatibility complex linked databases and prediction tools for designing vaccines.
Singh SP; Mishra BN
Hum Immunol; 2016 Mar; 77(3):295-306. PubMed ID: 26585361
[TBL] [Abstract][Full Text] [Related]
8. T-cell epitope prediction: rescaling can mask biological variation between MHC molecules.
MacNamara A; Kadolsky U; Bangham CR; Asquith B
PLoS Comput Biol; 2009 Mar; 5(3):e1000327. PubMed ID: 19300484
[TBL] [Abstract][Full Text] [Related]
9. 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]
10. In silico analysis of MHC-I restricted epitopes of Chikungunya virus proteins: Implication in understanding anti-CHIKV CD8(+) T cell response and advancement of epitope based immunotherapy for CHIKV infection.
Pratheek BM; Suryawanshi AR; Chattopadhyay S; Chattopadhyay S
Infect Genet Evol; 2015 Apr; 31():118-26. PubMed ID: 25643869
[TBL] [Abstract][Full Text] [Related]
11. Learning MHC I--peptide binding.
Jojic N; Reyes-Gomez M; Heckerman D; Kadie C; Schueler-Furman O
Bioinformatics; 2006 Jul; 22(14):e227-35. PubMed ID: 16873476
[TBL] [Abstract][Full Text] [Related]
12. MHCPred 2.0: an updated quantitative T-cell epitope prediction server.
Guan P; Hattotuwagama CK; Doytchinova IA; Flower DR
Appl Bioinformatics; 2006; 5(1):55-61. PubMed ID: 16539539
[TBL] [Abstract][Full Text] [Related]
13. Improved methods for predicting peptide binding affinity to MHC class II molecules.
Jensen KK; Andreatta M; Marcatili P; Buus S; Greenbaum JA; Yan Z; Sette A; Peters B; Nielsen M
Immunology; 2018 Jul; 154(3):394-406. PubMed ID: 29315598
[TBL] [Abstract][Full Text] [Related]
14. Toward the atomistic simulation of T cell epitopes automated construction of MHC: peptide structures for free energy calculations.
Todman SJ; Halling-Brown MD; Davies MN; Flower DR; Kayikci M; Moss DS
J Mol Graph Model; 2008 Feb; 26(6):957-61. PubMed ID: 17766153
[TBL] [Abstract][Full Text] [Related]
15. ProPred1: prediction of promiscuous MHC Class-I binding sites.
Singh H; Raghava GP
Bioinformatics; 2003 May; 19(8):1009-14. PubMed ID: 12761064
[TBL] [Abstract][Full Text] [Related]
16. A Novel Peptide Binding Prediction Approach for HLA-DR Molecule Based on Sequence and Structural Information.
Li Z; Zhao Y; Pan G; Tang J; Guo F
Biomed Res Int; 2016; 2016():3832176. PubMed ID: 27340658
[TBL] [Abstract][Full Text] [Related]
17. A systematic assessment of MHC class II peptide binding predictions and evaluation of a consensus approach.
Wang P; Sidney J; Dow C; Mothé B; Sette A; Peters B
PLoS Comput Biol; 2008 Apr; 4(4):e1000048. PubMed ID: 18389056
[TBL] [Abstract][Full Text] [Related]
18. DynaPred: a structure and sequence based method for the prediction of MHC class I binding peptide sequences and conformations.
Antes I; Siu SW; Lengauer T
Bioinformatics; 2006 Jul; 22(14):e16-24. PubMed ID: 16873467
[TBL] [Abstract][Full Text] [Related]
19. Methods and protocols for prediction of immunogenic epitopes.
Tong JC; Tan TW; Ranganathan S
Brief Bioinform; 2007 Mar; 8(2):96-108. PubMed ID: 17077136
[TBL] [Abstract][Full Text] [Related]
20. 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]
[Next] [New Search]
