Henrik Nielsen

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Søren BrunakProfessor of Disease Systems Biology, University of CopenhagenVerified email at cpr.ku.dk
Gunnar von HeijneStockholm UniversityVerified email at dbb.su.se
José Juan Almagro ArmenterosPostdoc, Stanford UniversityVerified email at stanford.edu
Ole WintherBiology, Univ of Copenhagen, Genomic Medicine, Rigshospitalet and Technical University of DenmarkVerified email at bio.ku.dk
Olof EmanuelssonAssociate professor, Royal Institute of Technology (KTH), StockholmVerified email at kth.se
Casper Kaae SønderbyFounder@twig.energy, ML/DL Research ScientistVerified email at twig.energy
Jacob EngelbrechtSenior Advisor, Danish Ministry of TaxationVerified email at engelbrecht.dk
Thomas Nordahl PetersenDTU Food, National Food Institute, DenmarkVerified email at food.dtu.dk
Konstantinos Tsirigos, PhD Bioinforma...Cognizant DenmarkVerified email at cognizant.com
Anders KroghDepartment of Computer Science and Center for Health Data Science, University of CopenhagenVerified email at di.ku.dk
Alexander Rosenberg JohansenStanford UniversityVerified email at stanford.edu
Søren Kaae SønderbyVerified email at bio.ku.dk
Morten NielsenDepartment of Health Technology, The Technical University ofVerified email at cbs.dtu.dk
Pierre BaldiProfessor, University of California, IrvineVerified email at ics.uci.edu
Vanessa JurtzNovo Nordisk A/SVerified email at novonordisk.com
Tracy PalmerProfessor of Microbiology, Newcastle UniversityVerified email at newcastle.ac.uk
Lars Juhl JensenUniversity of CopenhagenVerified email at cpr.ku.dk
Nikolaj Sorgenfrei BlomSenior Researcher, DTUVerified email at dtu.dk
Alfonso ValenciaICREA Professor. Barcelona Supercomputing Center.Verified email at bsc.es
Christopher T. WorkmanTechnical University of Denmark, Department of Biotechnology and BiomedicineVerified email at dtu.dk

Henrik Nielsen

Associate Professor, Department of Health Technology, Technical University of Denmark

Verified email at dtu.dk - Homepage

Bioinformatics Signal Peptides Protein Sorting Introns Start Codons


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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	9636	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	7850	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	6707	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	5049	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	3694	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	2913	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	2489	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	2103	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	1286	2003
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	851	1997
DeepLoc: prediction of protein subcellular localization using deep learning JJ Almagro Armenteros, CK Sønderby, SK Sønderby, H Nielsen, ... Bioinformatics 33 (21), 3387-3395, 2017	828	2017
Predicting Secretory Proteins with SignalP H Nielsen Protein Function Prediction. Methods in Molecular Biology 1611, 59-73, 2017	784	2017
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	777	1999
Prediction of signal peptides and signal anchors by a hidden Markov model. H Nielsen, A Krogh Ismb 6, 122-130, 1998	726	1998
Prediction of twin-arginine signal peptides JD Bendtsen, H Nielsen, D Widdick, T Palmer, S Brunak BMC bioinformatics 6 (1), 1-9, 2005	589	2005
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	470	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	453	2002
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	437	2019
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	392	2022
Neural network prediction of translation initiation sites in eukaryotes: perspectives for EST and genome analysis. AG Pedersen, H Nielsen Ismb 5, 226-233, 1997	383	1997

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