Ole Winther

Ole Winther

Professor with special responsibilities, Visiting professor, Professor MSO


  1. 2021
  2. Published

    The effect of smartphone-based monitoring and treatment on the rate and duration of psychiatric readmission in patients with unipolar depressive disorder: The RADMIS randomized controlled trial

    Tønning, M. L., Faurholt-Jepsen, Maria , Frost, M., Martiny, Klaus, Tuxen, N., Rosenberg, N., Busk, J., Winther, Ole, Melbye, S. A., Thaysen-Petersen, D., Aamund, K. A., Tolderlundh, L., Bardram, J. E. & Kessing, Lars Vedel, 2021, In: Journal of Affective Disorders. 282, p. 354-363 10 p.

    Research output: Contribution to journalJournal articleResearchpeer-review

  3. 2022
  4. Published

    Calibrated uncertainty for molecular property prediction using ensembles of message passing neural networks

    Busk, J., Jørgensen, P. B., Bhowmik, A., Schmidt, M. N., Winther, Ole & Vegge, T., 2022, In: Machine Learning: Science and Technology. 3, 1, 12 p., 015012.

    Research output: Contribution to journalJournal articleResearchpeer-review

  5. Published

    DeepLoc 2.0: multi-label subcellular localization prediction using protein language models

    Thumuluri, V., Almagro Armenteros, J. J., Johansen, A. R., Nielsen, H. & Winther, Ole, 2022, In: Nucleic Acids Research. 50, W1, p. W228-W234

    Research output: Contribution to journalJournal articleResearchpeer-review

  6. Published

    Interpretable autoencoders trained on single cell sequencing data can transfer directly to data from unseen tissues

    Walbech, J. S., Kinalis, S., Winther, Ole, Nielsen, Finn Cilius & Bagger, F. O., 2022, In: Cells. 11, 12 p., 85.

    Research output: Contribution to journalJournal articleResearchpeer-review

  7. Published

    NetSurfP-3.0: accurate and fast prediction of protein structural features by protein language models and deep learning

    Høie, M. H., Kiehl, E. N., Petersen, Bent, Nielsen, M., Winther, Ole, Nielsen, H., Hallgren, J. & Marcatili, P., 2022, In: Nucleic Acids Research. 50, W1, p. W510-W515 6 p.

    Research output: Contribution to journalJournal articleResearchpeer-review

  8. Published

    SignalP 6.0 predicts all five types of signal peptides using protein language models

    Teufel, Felix Georg, Almagro Armenteros, J. J., Johansen, A. R., Gíslason, M. H., Pihl, S. I., Tsirigos, Konstantinos, Winther, Ole, Brunak, Søren, von Heijne, G. & Nielsen, H., 2022, In: Nature Biotechnology. 40, p. 1023-1025

    Research output: Contribution to journalComment/debateResearch

  9. Published

    Transfer learning reveals sequence determinants of regulatory element accessibility

    Salvatore, Marco, Horlacher, M., Winther, Ole & Andersson, Robin, 2022, bioRxiv, 24 p.

    Research output: Working paperPreprintResearch

  10. Published

    Transition1x: a dataset for building generalizable reactive machine learning potentials

    Schreiner, M., Bhowmik, A., Vegge, T., Busk, J. & Winther, Ole, 2022, In: Scientific Data. 9, 1, 9 p., 779.

    Research output: Contribution to journalJournal articleResearchpeer-review

  11. 2023
  12. Published

    Deep integrative models for large-scale human genomics

    Sigurdsson, Arnór Ingi, Louloudis, Ioannis, Banasik, Karina, Westergaard, David, Winther, Ole, Lund, O., Ostrowski, Sisse Rye, Erikstrup, C., Pedersen, Ole Birger Vesterager, Nyegaard, Mette, Brunak, Søren, Vilhjálmsson, B. & Rasmussen, Simon, 2023, In: Nucleic Acids Symposium Series. 51, 12, 16 p.

    Research output: Contribution to journalJournal articleResearchpeer-review

  13. Published

    DeepPeptide predicts cleaved peptides in proteins using conditional random fields

    Teufel, Felix Georg, Refsgaard, J. C., Madsen, C. T., Stahlhut, C., Grønborg, M., Winther, Ole & Madsen, D., 2023, In: Bioinformatics (Oxford, England). 39, 10, 6 p., btad616.

    Research output: Contribution to journalJournal articleResearchpeer-review

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