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Items: 1 to 20 of 29

1.

A deimmunised form of the ribotoxin, α-sarcin, lacking CD4+ T cell epitopes and its use as an immunotoxin warhead.

Jones TD, Hearn AR, Holgate RG, Kozub D, Fogg MH, Carr FJ, Baker MP, Lacadena J, Gehlsen KR.

Protein Eng Des Sel. 2016 Aug 29. [Epub ahead of print]

2.

Autoimmune Responses to Soluble Aggregates of Amyloidogenic Proteins Involved in Neurodegenerative Diseases: Overlapping Aggregation Prone and Autoimmunogenic regions.

Kumar S, Thangakani AM, Nagarajan R, Singh SK, Velmurugan D, Gromiha MM.

Sci Rep. 2016 Feb 29;6:22258. doi: 10.1038/srep22258.

3.

Alleles of HLA-DRB1*04 Associated with Pulmonary Tuberculosis in Amazon Brazilian Population.

Souza de Lima D, Morishi Ogusku M, Porto Dos Santos M, de Melo Silva CM, Alves de Almeida V, Assumpção Antunes I, Boechat AL, Ramasawmy R, Sadahiro A.

PLoS One. 2016 Feb 22;11(2):e0147543. doi: 10.1371/journal.pone.0147543. eCollection 2016.

4.

Enhanced Detection of Antigen-Specific CD4+ T Cells Using Altered Peptide Flanking Residue Peptide-MHC Class II Multimers.

Holland CJ, Dolton G, Scurr M, Ladell K, Schauenburg AJ, Miners K, Madura F, Sewell AK, Price DA, Cole DK, Godkin AJ.

J Immunol. 2015 Dec 15;195(12):5827-36. doi: 10.4049/jimmunol.1402787. Epub 2015 Nov 9.

5.
6.

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. doi: 10.1007/s00251-015-0873-y. Epub 2015 Sep 29.

7.

Prediction of epitope-based peptides for the utility of vaccine development from fusion and glycoprotein of nipah virus using in silico approach.

Sakib MS, Islam MR, Hasan AK, Nabi AH.

Adv Bioinformatics. 2014;2014:402492. doi: 10.1155/2014/402492. Epub 2014 Jul 24.

8.

The versatility of the αβ T-cell antigen receptor.

Bhati M, Cole DK, McCluskey J, Sewell AK, Rossjohn J.

Protein Sci. 2014 Mar;23(3):260-72. doi: 10.1002/pro.2412. Epub 2014 Jan 28. Review.

9.

Molecular dynamics simulations to provide insights into epitopes coupled to the soluble and membrane-bound MHC-II complexes.

Bello M, Correa-Basurto J.

PLoS One. 2013 Aug 19;8(8):e72575. doi: 10.1371/journal.pone.0072575. eCollection 2013.

10.

Re-Directing CD4(+) T Cell Responses with the Flanking Residues of MHC Class II-Bound Peptides: The Core is Not Enough.

Holland CJ, Cole DK, Godkin A.

Front Immunol. 2013 Jul 1;4:172. doi: 10.3389/fimmu.2013.00172. eCollection 2013.

11.

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:S13. doi: 10.1186/1471-2105-14-S2-S13. Epub 2013 Jan 21.

12.

Flanking residues are central to DO11.10 T cell hybridoma stimulation by ovalbumin 323-339.

Roy BM, Zhukov DV, Maynard JA.

PLoS One. 2012;7(10):e47585. doi: 10.1371/journal.pone.0047585. Epub 2012 Oct 23.

13.

Modification of the carboxy-terminal flanking region of a universal influenza epitope alters CD4⁺ T-cell repertoire selection.

Cole DK, Gallagher K, Lemercier B, Holland CJ, Junaid S, Hindley JP, Wynn KK, Gostick E, Sewell AK, Gallimore AM, Ladell K, Price DA, Gougeon ML, Godkin A.

Nat Commun. 2012 Feb 7;3:665. doi: 10.1038/ncomms1665.

14.

NNAlign: a web-based prediction method allowing non-expert end-user discovery of sequence motifs in quantitative peptide data.

Andreatta M, Schafer-Nielsen C, Lund O, Buus S, Nielsen M.

PLoS One. 2011;6(11):e26781. doi: 10.1371/journal.pone.0026781. Epub 2011 Nov 2.

15.

Dana-Farber repository for machine learning in immunology.

Zhang GL, Lin HH, Keskin DB, Reinherz EL, Brusic V.

J Immunol Methods. 2011 Nov 30;374(1-2):18-25. doi: 10.1016/j.jim.2011.07.007. Epub 2011 Jul 18.

16.

Genetic engineering of trimers of hypoallergenic fragments of the major birch pollen allergen, Bet v 1, for allergy vaccination.

Vrtala S, Fohr M, Campana R, Baumgartner C, Valent P, Valenta R.

Vaccine. 2011 Mar 3;29(11):2140-8. doi: 10.1016/j.vaccine.2010.12.080. Epub 2011 Jan 5.

17.

State of the art and challenges in sequence based T-cell epitope prediction.

Lundegaard C, Hoof I, Lund O, Nielsen M.

Immunome Res. 2010 Nov 3;6 Suppl 2:S3. doi: 10.1186/1745-7580-6-S2-S3.

18.

MHC class II epitope predictive algorithms.

Nielsen M, Lund O, Buus S, Lundegaard C.

Immunology. 2010 Jul;130(3):319-28. doi: 10.1111/j.1365-2567.2010.03268.x. Epub 2010 Apr 12. Review.

19.

Limitations of Ab initio predictions of peptide binding to MHC class II molecules.

Zhang H, Wang P, Papangelopoulos N, Xu Y, Sette A, Bourne PE, Lund O, Ponomarenko J, Nielsen M, Peters B.

PLoS One. 2010 Feb 17;5(2):e9272. doi: 10.1371/journal.pone.0009272.

20.

NN-align. An artificial neural network-based alignment algorithm for MHC class II peptide binding prediction.

Nielsen M, Lund O.

BMC Bioinformatics. 2009 Sep 18;10:296. doi: 10.1186/1471-2105-10-296.

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