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Results: 1 to 20 of 108

1.

Strength in numbers: achieving greater accuracy in MHC-I binding prediction by combining the results from multiple prediction tools.

Trost B, Bickis M, Kusalik A.

Immunome Res. 2007 Mar 24;3:5.PMID: 17381846 [PubMed]Related articlesFree article

2.

Evaluation of MHC-II peptide binding prediction servers: applications for vaccine research.

Lin HH, Zhang GL, Tongchusak S, Reinherz EL, Brusic V.

BMC Bioinformatics. 2008 Dec 12;9 Suppl 12:S22.PMID: 19091022 [PubMed - indexed for MEDLINE]Related articlesFree article

3.

Prediction of MHC class I binding peptides, using SVMHC.

Dönnes P, Elofsson A.

BMC Bioinformatics. 2002 Sep 11;3:25.PMID: 12225620 [PubMed - indexed for MEDLINE]Related articlesFree article

4.

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 4;8:238.PMID: 17608956 [PubMed - indexed for MEDLINE]Related articlesFree article

5.

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 9;2(6):e65. Epub 2006 Jun 9.PMID: 16789818 [PubMed - indexed for MEDLINE]Related articlesFree article

6.

Evaluation of MHC class I peptide binding prediction servers: applications for vaccine research.

Lin HH, Ray S, Tongchusak S, Reinherz EL, Brusic V.

BMC Immunol. 2008 Mar 16;9:8.PMID: 18366636 [PubMed - indexed for MEDLINE]Related articlesFree article

7.

Automated generation and evaluation of specific MHC binding predictive tools: ARB matrix applications.

Bui HH, Sidney J, Peters B, Sathiamurthy M, Sinichi A, Purton KA, Mothé BR, Chisari FV, Watkins DI, Sette A.

Immunogenetics. 2005 Jun;57(5):304-14. Epub 2005 May 3.PMID: 15868141 [PubMed - indexed for MEDLINE]Related articles

8.

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 1;36(Web Server issue):W509-12. Epub 2008 May 7.PMID: 18463140 [PubMed - indexed for MEDLINE]Related articlesFree article

9.

POPI: predicting immunogenicity of MHC class I binding peptides by mining informative physicochemical properties.

Tung CW, Ho SY.

Bioinformatics. 2007 Apr 15;23(8):942-9. Epub 2007 Mar 24.PMID: 17384427 [PubMed - indexed for MEDLINE]Related articlesFree article

10.

Prediction of MHC-binding peptides of flexible lengths from sequence-derived structural and physicochemical properties.

Cui J, Han LY, Lin HH, Zhang HL, Tang ZQ, Zheng CJ, Cao ZW, Chen YZ.

Mol Immunol. 2007 Feb;44(5):866-77. Epub 2006 Jun 27.PMID: 16806474 [PubMed - indexed for MEDLINE]Related articles

11.

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(4):e1000048.PMID: 18389056 [PubMed - indexed for MEDLINE]Related articlesFree article

12.

A hybrid approach for predicting promiscuous MHC class I restricted T cell epitopes.

Bhasin M, Raghava GP.

J Biosci. 2007 Jan;32(1):31-42. Erratum in: J Biosci. 2007 Jun;32(4):805. PMID: 17426378 [PubMed - indexed for MEDLINE]Related articlesFree article

13.

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 Jan-Feb;47(1):234-8.PMID: 17238269 [PubMed - indexed for MEDLINE]Related articles

14.

Quantitative predictions of peptide binding to any HLA-DR molecule of known sequence: NetMHCIIpan.

Nielsen M, Lundegaard C, Blicher T, Peters B, Sette A, Justesen S, Buus S, Lund O.

PLoS Comput Biol. 2008 Jul 4;4(7):e1000107.PMID: 18604266 [PubMed - indexed for MEDLINE]Related articlesFree article

15.

Predicting peptides binding to MHC class II molecules using multi-objective evolutionary algorithms.

Rajapakse M, Schmidt B, Feng L, Brusic V.

BMC Bioinformatics. 2007 Nov 22;8:459.PMID: 18031584 [PubMed - indexed for MEDLINE]Related articlesFree article

16.

Accurate approximation method for prediction of class I MHC affinities for peptides of length 8, 10 and 11 using prediction tools trained on 9mers.

Lundegaard C, Lund O, Nielsen M.

Bioinformatics. 2008 Jun 1;24(11):1397-8. Epub 2008 Apr 14.PMID: 18413329 [PubMed - indexed for MEDLINE]Related articlesFree article

17.

A critical cross-validation of high throughput structural binding prediction methods for pMHC.

Knapp B, Omasits U, Frantal S, Schreiner W.

J Comput Aided Mol Des. 2009 May;23(5):301-7. Epub 2009 Feb 5.PMID: 19194661 [PubMed - indexed for MEDLINE]Related articles

18.

'Unite and conquer': enhanced prediction of protein subcellular localization by integrating multiple specialized tools.

Shen YQ, Burger G.

BMC Bioinformatics. 2007 Oct 29;8:420.PMID: 17967180 [PubMed - indexed for MEDLINE]Related articlesFree article

19.

Predicting MHC class I epitopes in large datasets.

Roomp K, Antes I, Lengauer T.

BMC Bioinformatics. 2010 Feb 17;11:90.PMID: 20163709 [PubMed - in process]Related articlesFree article

20.

MHC-BPS: MHC-binder prediction server for identifying peptides of flexible lengths from sequence-derived physicochemical properties.

Cui J, Han LY, Lin HH, Tang ZQ, Jiang L, Cao ZW, Chen YZ.

Immunogenetics. 2006 Aug;58(8):607-13. Epub 2006 Jul 11.PMID: 16832638 [PubMed - indexed for MEDLINE]Related articles

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