Author

Vanessa Isabell Jurtz

Technical University of DenmarkORCID 0000-0003-4452-6605Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 3

Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Assay:protein sequence· 2 Research Focus:protein structure prediction· 2 Approach:statistical model· 2 Organism:human· 1 Research Focus:sequence-to-function modeling· 1

Frequent Co-Authors

Morten NielseniD· 3 shared Paolo MarcatiliiD· 3 shared Bjoern PetersiD· 2 shared Kamilla Kjærgaard Jensen· 2 shared Martin Closter Jespersen· 2 shared Amalie Kai BentzeniD· 1 shared Bent PeterseniD· 1 shared Casper Kaae Sønderby· 1 shared

Activity by Year

2017-2019 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 36 mutual co-author links

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3 shared papersBioinformatics

Morten NielsenORCID

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3 papers

Recent·Most cited

BioinformaticsProteins Structure Function and BioinformaticsPeer-reviewedFeb 20, 2019

NetSurfP-2.0: improved prediction of protein structural features by integrated deep learning

Michael Schantz Klausen, Martin Closter Jespersen, Henrik Nielsen…·Paolo Marcatili

NetSurfP-2.0 improves prediction of protein structural features with higher accuracy and faster runtime than previous versions.

574 citationstop 1%

protein sequencedeep learning

𝕏 PostBluesky

BioinformaticsbioRxivPreprintOct 3, 2018

NetTCR: sequence-based prediction of TCR binding to peptide-MHC complexes using convolutional neural networks

Vanessa Isabell Jurtz, Leon Eyrich Jessen, Amalie Kai Bentzen…·Morten Nielsen

A sequence-only convolutional network trained on T cell receptor (TCR)-peptide pairs for HLA-A*02:01 can single out TCRs that bind a target peptide among many non-binding ones.

118 citations

humanprotein sequence

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BioinformaticsThe Journal of ImmunologyPeer-reviewedOct 4, 2017

NetMHCpan 4.0: Improved peptide-MHC class I interaction predictions integrating eluted ligand and peptide binding affinity data

Vanessa Isabell Jurtz, Sinu Paul, Massimo Andreatta…·Morten Nielsen

NetMHCpan-4.0 improves peptide-MHC class I interaction predictions by integrating binding affinity and eluted ligand data, enhancing identification of naturally processed ligands and T cell epitopes.

1,477 citationstop 1%

statistical modelprotein structure prediction

𝕏 PostBluesky