Jurtz V - Search Results

1

An Analysis of Natural T Cell Responses to Predicted Tumor Neoepitopes.

Bjerregaard AM, Nielsen M, Jurtz V, Barra CM, Hadrup SR, Szallasi Z, Eklund AC. Bjerregaard AM, et al. Among authors: jurtz v. Front Immunol. 2017 Nov 15;8:1566. doi: 10.3389/fimmu.2017.01566. eCollection 2017. Front Immunol. 2017. PMID: 29187854 Free PMC article.

2

Corrigendum: An Analysis of Natural T Cell Responses to Predicted Tumor Neoepitopes.

Bjerregaard AM, Nielsen M, Jurtz V, Barra CM, Hadrup SR, Szallasi Z, Eklund AC. Bjerregaard AM, et al. Among authors: jurtz v. Front Immunol. 2018 May 14;9:1007. doi: 10.3389/fimmu.2018.01007. eCollection 2018. Front Immunol. 2018. PMID: 29795801 Free PMC article.

3

NetMHCpan-4.0: Improved Peptide-MHC Class I Interaction Predictions Integrating Eluted Ligand and Peptide Binding Affinity Data.

Jurtz V, Paul S, Andreatta M, Marcatili P, Peters B, Nielsen M. Jurtz V, et al. J Immunol. 2017 Nov 1;199(9):3360-3368. doi: 10.4049/jimmunol.1700893. Epub 2017 Oct 4. J Immunol. 2017. PMID: 28978689 Free PMC article.

4

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. Paul S, et al. Among authors: jurtz v. Front Immunol. 2018 Aug 6;9:1795. doi: 10.3389/fimmu.2018.01795. eCollection 2018. Front Immunol. 2018. PMID: 30127785 Free PMC article.

5

Machine learning reveals a non-canonical mode of peptide binding to MHC class II molecules.

Andreatta M, Jurtz VI, Kaever T, Sette A, Peters B, Nielsen M. Andreatta M, et al. Immunology. 2017 Oct;152(2):255-264. doi: 10.1111/imm.12763. Epub 2017 Jun 19. Immunology. 2017. PMID: 28542831 Free PMC article.

6

NetH2pan: A Computational Tool to Guide MHC Peptide Prediction on Murine Tumors.

DeVette CI, Andreatta M, Bardet W, Cate SJ, Jurtz VI, Jackson KW, Welm AL, Nielsen M, Hildebrand WH. DeVette CI, et al. Cancer Immunol Res. 2018 Jun;6(6):636-644. doi: 10.1158/2326-6066.CIR-17-0298. Epub 2018 Apr 3. Cancer Immunol Res. 2018. PMID: 29615400 Free PMC article.

7

NetTCR-2.0 enables accurate prediction of TCR-peptide binding by using paired TCRα and β sequence data.

Montemurro A, Schuster V, Povlsen HR, Bentzen AK, Jurtz V, Chronister WD, Crinklaw A, Hadrup SR, Winther O, Peters B, Jessen LE, Nielsen M. Montemurro A, et al. Among authors: jurtz v. Commun Biol. 2021 Sep 10;4(1):1060. doi: 10.1038/s42003-021-02610-3. Commun Biol. 2021. PMID: 34508155 Free PMC article.

8

A generic deep convolutional neural network framework for prediction of receptor-ligand interactions-NetPhosPan: application to kinase phosphorylation prediction.

Fenoy E, Izarzugaza JMG, Jurtz V, Brunak S, Nielsen M. Fenoy E, et al. Among authors: jurtz v. Bioinformatics. 2019 Apr 1;35(7):1098-1107. doi: 10.1093/bioinformatics/bty715. Bioinformatics. 2019. PMID: 30169744

9

IEDB-AR: immune epitope database-analysis resource in 2019.

Dhanda SK, Mahajan S, Paul S, Yan Z, Kim H, Jespersen MC, Jurtz V, Andreatta M, Greenbaum JA, Marcatili P, Sette A, Nielsen M, Peters B. Dhanda SK, et al. Among authors: jurtz v. Nucleic Acids Res. 2019 Jul 2;47(W1):W502-W506. doi: 10.1093/nar/gkz452. Nucleic Acids Res. 2019. PMID: 31114900 Free PMC article.

10

MetaPhinder-Identifying Bacteriophage Sequences in Metagenomic Data Sets.

Jurtz VI, Villarroel J, Lund O, Voldby Larsen M, Nielsen M. Jurtz VI, et al. PLoS One. 2016 Sep 29;11(9):e0163111. doi: 10.1371/journal.pone.0163111. eCollection 2016. PLoS One. 2016. PMID: 27684958 Free PMC article.

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