Ole Winther

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Casper Kaae SønderbyFounder@twig.energy, ML/DL Research ScientistVerified email at twig.energy
José Juan Almagro ArmenterosPostdoc, Stanford UniversityVerified email at stanford.edu
Søren Kaae SønderbyVerified email at twig.energy
Lars Kai HansenProfessor, Cognitive Systems, DTU Compute, Technical University of DenmarkVerified email at dtu.dk
Henrik NielsenAssociate Professor, Department of Health Technology, Technical University of DenmarkVerified email at dtu.dk
Gunnar von HeijneStockholm UniversityVerified email at dbb.su.se
Lars MaaløeCo-Founder & CTO @ Corti | Adj. Assoc. Professor of Machine Learning @ DTUVerified email at corti.ai
Søren BrunakProfessor of Disease Systems Biology, University of CopenhagenVerified email at cpr.ku.dk
Alexander JohansenStanford UniversityVerified email at stanford.edu
Frederik Otzen BaggerUniversity of Cambridge and EMBL-EBIVerified email at ebi.ac.uk
Konstantinos Tsirigos, PhD Bioinforma...DTU BiosustainVerified email at dtu.dk
Anders KroghDepartment of Computer Science and Center for Health Data Science, University of CopenhagenVerified email at di.ku.dk
Thomas Nordahl PetersenDTU Food, National Food Institute, DenmarkVerified email at food.dtu.dk
Jonas BuskTechnical University of DenmarkVerified email at dtu.dk
Marco FraccaroTechnical University of DenmarkVerified email at dtu.dk
Nicolas RapindenmarkVerified email at ngc.dk
Mikkel N. SchmidtTechnical University of DenmarkVerified email at dtu.dk
Ricardo HenaoDuke UniversityVerified email at duke.edu
Lars Vedel KessingProfessor of Psychiatry, Psychiatric Center Copenhagen and University of Copenhagen, DenmarkVerified email at regionh.dk
Valentin LiévinGoogle DeepMindVerified email at google.com

Ole Winther

Biology, Univ of Copenhagen, Genomic Medicine, Rigshospitalet and Technical University of Denmark

Verified email at bio.ku.dk - Homepage

machine learning bioinformatics deep learning artificial intelligence


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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	3965	2019
Autoencoding beyond pixels using a learned similarity metric ABL Larsen, SK Sønderby, H Larochelle, O Winther International conference on machine learning, 1558-1566, 2016	2706	2016
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	1555	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	1129	2017
Ladder variational autoencoders CK Sønderby, T Raiko, L Maaløe, SK Sønderby, O Winther Advances in neural information processing systems 29, 2016	1128*	2016
JASPAR, the open access database of transcription factor-binding profiles: new content and tools in the 2008 update JC Bryne, E Valen, MHE Tang, T Marstrand, O Winther, I da Piedade, ... Nucleic acids research 36 (suppl_1), D102-D106, 2007	841	2007
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	827	2019
DeepTMHMM predicts alpha and beta transmembrane proteins using deep neural networks J Hallgren, KD Tsirigos, MD Pedersen, JJ Almagro Armenteros, ... BioRxiv, 2022.04. 08.487609, 2022	706	2022
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	581	2019
Auxiliary deep generative models L Maaløe, CK Sønderby, SK Sønderby, O Winther International conference on machine learning, 1445-1453, 2016	521	2016
Sequential neural models with stochastic layers M Fraccaro, SK Sønderby, U Paquet, O Winther Advances in neural information processing systems 29, 2016	475	2016
The transcriptional network that controls growth arrest and differentiation in a human myeloid leukemia cell line Nature genetics 41 (5), 553-562, 2009	422	2009
Improved metagenome binning and assembly using deep variational autoencoders JN Nissen, J Johansen, RL Allesøe, CK Sønderby, JJA Armenteros, ... Nature biotechnology 39 (5), 555-560, 2021	395	2021
A disentangled recognition and nonlinear dynamics model for unsupervised learning M Fraccaro, S Kamronn, U Paquet, O Winther Advances in neural information processing systems 30, 2017	365	2017
DeepLoc 2.0: multi-label subcellular localization prediction using protein language models V Thumuluri, JJ Almagro Armenteros, AR Johansen, H Nielsen, O Winther Nucleic acids research 50 (W1), W228-W234, 2022	359	2022
Gaussian processes for classification: Mean-field algorithms M Opper, O Winther Neural computation 12 (11), 2655-2684, 2000	333	2000
BloodSpot: a database of gene expression profiles and transcriptional programs for healthy and malignant haematopoiesis FO Bagger, D Sasivarevic, SH Sohi, LG Laursen, S Pundhir, CK Sønderby, ... Nucleic acids research 44 (D1), D917-D924, 2016	329	2016
Expectation consistent approximate inference. M Opper, O Winther, MJ Jordan Journal of Machine Learning Research 6 (12), 2005	296	2005
Bayesian non-negative matrix factorization MN Schmidt, O Winther, LK Hansen Independent Component Analysis and Signal Separation: 8th International …, 2009	291	2009
A Bayesian approach to on-line learning M Opper, O Winther On-line learning in neural networks, 363-378, 1999	280	1999

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