Henrik Nielsen
Henrik Nielsen
Associate Professor, Department of Health Technology, Technical University of Denmark
Verified email at - Homepage
Cited by
Cited by
SignalP 4.0: discriminating signal peptides from transmembrane regions
TN Petersen, S Brunak, G Von Heijne, H Nielsen
Nature methods 8 (10), 785-786, 2011
Improved prediction of signal peptides: SignalP 3.0
JD Bendtsen, H Nielsen, G Von Heijne, S Brunak
Journal of molecular biology 340 (4), 783-795, 2004
Identification of prokaryotic and eukaryotic signal peptides and prediction of their cleavage sites.
H Nielsen, J Engelbrecht, S Brunak, G Von Heijne
Protein engineering 10 (1), 1-6, 1997
Predicting subcellular localization of proteins based on their N-terminal amino acid sequence
O Emanuelsson, H Nielsen, S Brunak, G Von Heijne
Journal of molecular biology 300 (4), 1005-1016, 2000
Locating proteins in the cell using TargetP, SignalP and related tools
O Emanuelsson, S Brunak, G von Heijne, H Nielsen
Nature protocols 2 (4), 953-971, 2007
SignalP 5.0 improves signal peptide predictions using deep neural networks
JJ Almagro Armenteros, KD Tsirigos, CK Sønderby, TN Petersen, ...
Nature biotechnology 37 (4), 420-423, 2019
Assessing the accuracy of prediction algorithms for classification: an overview
P Baldi, S Brunak, Y Chauvin, CAF Andersen, H Nielsen
Bioinformatics 16 (5), 412-424, 2000
ChloroP, a neural network‐based method for predicting chloroplast transit peptides and their cleavage sites
O Emanuelsson, H Nielsen, GV Heijne
Protein Science 8 (5), 978-984, 1999
Prediction of lipoprotein signal peptides in Gram‐negative bacteria
AS Juncker, H Willenbrock, G Von Heijne, S Brunak, H Nielsen, A Krogh
Protein Science 12 (8), 1652-1662, 2003
SignalP 6.0 predicts all five types of signal peptides using protein language models
F Teufel, JJ Almagro Armenteros, AR Johansen, MH Gíslason, SI Pihl, ...
Nature biotechnology 40 (7), 1023-1025, 2022
DeepLoc: prediction of protein subcellular localization using deep learning
JJ Almagro Armenteros, CK Sønderby, SK Sønderby, H Nielsen, ...
Bioinformatics 33 (21), 3387-3395, 2017
Predicting Secretory Proteins with SignalP
H Nielsen
Protein Function Prediction. Methods in Molecular Biology 1611, 59-73, 2017
A neural network method for identification of prokaryotic and eukaryotic signal peptides and prediction of their cleavage sites
H Nielsen, J Engelbrecht, S Brunak, G Von Heijne
International Journal of Neural Systems 8 (5-6), 581-599, 1997
Machine learning approaches for the prediction of signal peptides and other protein sorting signals
H Nielsen, S Brunak, G von Heijne
Protein engineering 12 (1), 3-9, 1999
Prediction of signal peptides and signal anchors by a hidden Markov model.
H Nielsen, A Krogh
Ismb 6, 122-130, 1998
Detecting sequence signals in targeting peptides using deep learning
JJA Armenteros, M Salvatore, O Emanuelsson, O Winther, G Von Heijne, ...
Life science alliance 2 (5), 2019
Prediction of twin-arginine signal peptides
JD Bendtsen, H Nielsen, D Widdick, T Palmer, S Brunak
BMC bioinformatics 6, 1-9, 2005
NetSurfP‐2.0: Improved prediction of protein structural features by integrated deep learning
MS Klausen, MC Jespersen, H Nielsen, KK Jensen, VI Jurtz, ...
Proteins: Structure, Function, and Bioinformatics 87 (6), 520-527, 2019
Prediction of human protein function from post-translational modifications and localization features
LJ Jensen, R Gupta, N Blom, D Devos, J Tamames, C Kesmir, H Nielsen, ...
Journal of molecular biology 319 (5), 1257-1265, 2002
Neural network prediction of translation initiation sites in eukaryotes: perspectives for EST and genome analysis.
AG Pedersen, H Nielsen
Ismb 5, 226-233, 1997
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