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Ole Winther
Ole Winther
Biology, Univ of Copenhagen, Genomic Medicine, Rigshospitalet and Technical University of Denmark
Email verificata su bio.ku.dk - Home page
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Citata da
Citata da
Anno
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
29132019
Autoencoding beyond pixels using a learned similarity metric
ABL Larsen, SK Sønderby, H Larochelle, O Winther
International conference on machine learning, 1558-1566, 2016
21202016
Ladder variational autoencoders
CK Sønderby, T Raiko, L Maaløe, SK Sønderby, O Winther
Advances in neural information processing systems 29, 2016
887*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
8282017
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
8062007
The transcriptional network that controls growth arrest and differentiation in a human myeloid leukemia cell line
Nature genetics 41 (5), 553-562, 2009
4732009
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
4702019
Auxiliary deep generative models
L Maaløe, CK Sønderby, SK Sønderby, O Winther
International conference on machine learning, 1445-1453, 2016
4652016
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
4372019
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
4062022
Sequential neural models with stochastic layers
M Fraccaro, SK Sønderby, U Paquet, O Winther
Advances in neural information processing systems 29, 2016
3852016
Gaussian processes for classification: Mean-field algorithms
M Opper, O Winther
Neural computation 12 (11), 2655-2684, 2000
3132000
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
2862017
Expectation consistent approximate inference.
M Opper, O Winther, MJ Jordan
Journal of Machine Learning Research 6 (12), 2005
2732005
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
2692016
Bayesian non-negative matrix factorization
MN Schmidt, O Winther, LK Hansen
Independent Component Analysis and Signal Separation: 8th International …, 2009
2642009
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
2532006
A Bayesian approach to on-line learning
M Opper, O Winther
Cambridge University Press, 1999
2521999
RSK is a principal effector of the RAS-ERK pathway for eliciting a coordinate promotile/invasive gene program and phenotype in epithelial cells
U Doehn, C Hauge, SR Frank, CJ Jensen, K Duda, JV Nielsen, ...
Molecular cell 35 (4), 511-522, 2009
2262009
Mean-field approaches to independent component analysis
PAFR Højen-Sørensen, O Winther, LK Hansen
Neural Computation 14 (4), 889-918, 2002
2112002
Il sistema al momento non può eseguire l'operazione. Riprova più tardi.
Articoli 1–20