Ole Winther

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Casper Kaae SønderbyFounder@twig.energy, ML/DL Research ScientistVerified email at twig.energy
Søren Kaae SønderbyVerified email at twig.energy
José Juan Almagro ArmenterosPostdoc, Stanford UniversityVerified email at stanford.edu
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
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
Frederik Otzen BaggerUniversity of Cambridge and EMBL-EBIVerified email at ebi.ac.uk
Gunnar von HeijneStockholm UniversityVerified email at dbb.su.se
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
Konstantinos Tsirigos, PhD Bioinforma...Cognizant DenmarkVerified email at cognizant.com
Marco FraccaroTechnical University of DenmarkVerified email at dtu.dk
Nicolas RapindenmarkVerified email at ngc.dk
Thomas Nordahl PetersenDTU Food, National Food Institute, DenmarkVerified email at food.dtu.dk
Ricardo HenaoKing Abdullah University of Science and Technology, Duke UniversityVerified email at duke.edu
Lars Vedel KessingProfessor of Psychiatry, Psychiatric Center Copenhagen and University of Copenhagen, DenmarkVerified email at regionh.dk
Jonas BuskTechnical University of DenmarkVerified email at dtu.dk
Albin SandelinThe Bioinformatics Centre, Department of Biology & BRIC, Copenhagen UniversityVerified email at binf.ku.dk
Finn Cilius NIelsenProfessorVerified email at regionh.dk

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	3320	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	2305	2016
Ladder variational autoencoders CK Sønderby, T Raiko, L Maaløe, SK Sønderby, O Winther Advances in neural information processing systems 29, 2016	969*	2016
DeepLoc: prediction of protein subcellular localization using deep learning JJ Almagro Armenteros, CK Sønderby, SK Sønderby, H Nielsen, ... Bioinformatics 33 (21), 3387-3395, 2017	948	2017
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	818	2007
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	728	2022
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	600	2019
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	487	2019
Auxiliary deep generative models L Maaløe, CK Sønderby, SK Sønderby, O Winther International conference on machine learning, 1445-1453, 2016	486	2016
Sequential neural models with stochastic layers M Fraccaro, SK Sønderby, U Paquet, O Winther Advances in neural information processing systems 29, 2016	423	2016
The transcriptional network that controls growth arrest and differentiation in a human myeloid leukemia cell line Nature genetics 41 (5), 553-562, 2009	414	2009
Gaussian processes for classification: Mean-field algorithms M Opper, O Winther Neural computation 12 (11), 2655-2684, 2000	316	2000
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	315	2017
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	288	2016
Expectation consistent approximate inference. M Opper, O Winther, MJ Jordan Journal of Machine Learning Research 6 (12), 2005	283	2005
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	274	2022
Bayesian non-negative matrix factorization MN Schmidt, O Winther, LK Hansen Independent Component Analysis and Signal Separation: 8th International …, 2009	271	2009
A Bayesian approach to on-line learning M Opper, O Winther Cambridge University Press, 1999	263	1999
Growth-rate regulated genes have profound impact on interpretation of transcriptome profiling in Saccharomyces cerevisiae B Regenberg, T Grotkjær, O Winther, A Fausbøll, M Åkesson, C Bro, ... Genome biology 7 (11), 1-13, 2006	255	2006
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	235*	2021

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