Ole Winther

D-Index & Metrics D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines.

Discipline name Citations Publications World Ranking National Ranking

Computer Science D-index 49 Citations 12,321 202 World Ranking 3811 National Ranking 11

Overview

What are the main themes of his work throughout his whole career to date

Completeness (order theory) and Generalization are all intertwined in Mathematical analysis research. Many of his studies on Generalization involve topics that are commonly interrelated, such as Mathematical analysis. Signal peptide and Protein sequencing are all intrinsically tied to his study in Peptide sequence. In his work, Ole Winther performs multidisciplinary research in Protein sequencing and Peptide sequence. While working on this project, Ole Winther studies both Gene and Signal peptide. Ole Winther merges Machine learning with Deep learning in his research. He performs integrative study on Deep learning and Machine learning in his works. His research on Artificial intelligence frequently connects to adjacent areas such as Pattern recognition (psychology). His Pattern recognition (psychology) study frequently links to related topics such as Artificial intelligence.

Ole Winther most often published in these fields:

Gene (50.00%)
Machine learning (50.00%)
Artificial intelligence (50.00%)

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

SignalP 5.0 improves signal peptide predictions using deep neural networks

Jose Juan Almagro Armenteros;Konstantinos D. Tsirigos;Casper Kaae Sønderby;Thomas Nordahl Petersen.
Nature Biotechnology (2019)

2312 Citations

Autoencoding beyond pixels using a learned similarity metric

Anders Boesen Lindbo Larsen;Søren Kaae Sønderby;Hugo Larochelle;Ole Winther.
international conference on machine learning (2016)

1015 Citations

JASPAR, the open access database of transcription factor-binding profiles: new content and tools in the 2008 update

Jan Christian Bryne;Eivind Valen;Man-Hung Eric Tang;Troels Torben Marstrand.
Nucleic Acids Research (2007)

800 Citations

DeepLoc: prediction of protein subcellular localization using deep learning.

Jose Juan Almagro Armenteros;Jose Juan Almagro Armenteros;Casper Kaae Sønderby;Søren Kaae Sønderby;Henrik Nielsen.
Bioinformatics (2017)

676 Citations

Ladder Variational Autoencoders

Casper Kaae Sønderby;Tapani Raiko;Lars Maaløe;Søren Kaae Sønderby.
neural information processing systems (2016)

502 Citations

The transcriptional network that controls growth arrest and differentiation in a human myeloid leukemia cell line

Harukazu Suzuki;Alistair R.R. Forrest;Erik Van Nimwegen;Carsten O. Daub.
Nature Genetics (2009)

469 Citations

Gaussian Processes for Classification: Mean-Field Algorithms

Manfred Opper;Ole Winther.
Neural Computation (2000)

335 Citations

NetSurfP-2.0: Improved prediction of protein structural features by integrated deep learning

Michael Schantz Klausen;Martin Closter Jespersen;Henrik Nielsen;Kamilla Kjærgaard Jensen.
Proteins (2019)

314 Citations

Detecting sequence signals in targeting peptides using deep learning.

Jose Juan Almagro Armenteros;Marco Salvatore;Marco Salvatore;Olof Emanuelsson;Olof Emanuelsson;Ole Winther;Ole Winther;Ole Winther.
Life Science Alliance (2019)

302 Citations

Bayesian Non-negative Matrix Factorization

Mikkel N. Schmidt;Ole Winther;Lars Kai Hansen.
international conference on independent component analysis and signal separation (2009)

255 Citations

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Ole Winther

D-Index & Metrics D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines.

Overview

What are the main themes of his work throughout his whole career to date

Ole Winther most often published in these fields:

Best Publications

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