Ole Winther

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Casper Kaae SønderbyFounder@twig.energy, ML/DL Research ScientistVerificeret mail på twig.energy
José Juan Almagro ArmenterosPostdoc, Stanford UniversityVerificeret mail på stanford.edu
Søren Kaae SønderbyVerificeret mail på twig.energy
Lars Kai HansenProfessor, Cognitive Systems, DTU Compute, Technical University of DenmarkVerificeret mail på dtu.dk
Henrik NielsenAssociate Professor, Department of Health Technology, Technical University of DenmarkVerificeret mail på dtu.dk
Gunnar von HeijneStockholm UniversityVerificeret mail på dbb.su.se
Lars MaaløeCo-Founder & CTO @ Corti | Adj. Assoc. Professor of Machine Learning @ DTUVerificeret mail på corti.ai
Søren BrunakProfessor of Disease Systems Biology, University of CopenhagenVerificeret mail på cpr.ku.dk
Alexander JohansenStanford UniversityVerificeret mail på stanford.edu
Frederik Otzen BaggerUniversity of Cambridge and EMBL-EBIVerificeret mail på ebi.ac.uk
Konstantinos Tsirigos, PhD Bioinforma...DTU BiosustainVerificeret mail på dtu.dk
Anders KroghDepartment of Computer Science and Center for Health Data Science, University of CopenhagenVerificeret mail på di.ku.dk
Thomas Nordahl PetersenDTU Food, National Food Institute, DenmarkVerificeret mail på food.dtu.dk
Jonas BuskTechnical University of DenmarkVerificeret mail på dtu.dk
Marco FraccaroTechnical University of DenmarkVerificeret mail på dtu.dk
Nicolas RapindenmarkVerificeret mail på ngc.dk
Mikkel N. SchmidtTechnical University of DenmarkVerificeret mail på dtu.dk
Ricardo HenaoDuke UniversityVerificeret mail på duke.edu
Lars Vedel KessingProfessor of Psychiatry, Psychiatric Center Copenhagen and University of Copenhagen, DenmarkVerificeret mail på regionh.dk
Finn Cilius NIelsenProfessorVerificeret mail på regionh.dk

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Ole Winther

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

Verificeret mail på bio.ku.dk - Startside

machine learning bioinformatics deep learning artificial intelligence


Titel Sortér efter henvisninger Sortér efter årstal Sortér efter titel	Citeret af Citeret af	År
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	3819	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	2623	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	1319	2022
Ladder variational autoencoders CK Sønderby, T Raiko, L Maaløe, SK Sønderby, O Winther Advances in neural information processing systems 29, 2016	1085*	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	1084	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	833	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	771	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	591	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	552	2019
Auxiliary deep generative models L Maaløe, CK Sønderby, SK Sønderby, O Winther International conference on machine learning, 1445-1453, 2016	512	2016
Sequential neural models with stochastic layers M Fraccaro, SK Sønderby, U Paquet, O Winther Advances in neural information processing systems 29, 2016	460	2016
The transcriptional network that controls growth arrest and differentiation in a human myeloid leukemia cell line Nature genetics 41 (5), 553-562, 2009	420	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	350	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	350	2017
Gaussian processes for classification: Mean-field algorithms M Opper, O Winther Neural computation 12 (11), 2655-2684, 2000	329	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	322	2016
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	293	2022
Expectation consistent approximate inference. M Opper, O Winther, MJ Jordan Journal of Machine Learning Research 6 (12), 2005	290	2005
Bayesian non-negative matrix factorization MN Schmidt, O Winther, LK Hansen Independent Component Analysis and Signal Separation: 8th International …, 2009	286	2009
A Bayesian approach to on-line learning M Opper, O Winther On-line learning in neural networks, 363-378, 1999	278	1999

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