Ole Winther

Ole Winther

Professor with special responsibilities, Professor MSO


  1. 2023
  2. Published

    Deorphanizing Peptides Using Structure Prediction

    Teufel, Felix Georg, Refsgaard, J. C., Kasimova, M. A., Deibler, K., Madsen, C. T., Stahlhut, C., Grønborg, M., Winther, Ole & Madsen, D., 2023, In: Journal of Chemical Information and Modeling. 63, 9, 5 p.

    Research output: Contribution to journalJournal articleResearchpeer-review

  3. Published

    DermX: An end-to-end framework for explainable automated dermatological diagnosis

    Jalaboi, R., Faye, F., Orbes-Arteaga, M., Jørgensen, D., Winther, Ole & Galimzianova, A., 2023, In: Medical Image Analysis. 83, 12 p., 102647.

    Research output: Contribution to journalJournal articleResearchpeer-review

  4. E-pub ahead of print

    Explainable Image Quality Assessments in Teledermatological Photography

    Jalaboi, R., Winther, Ole & Galimzianova, A., 2023, (E-pub ahead of print) In: Telemedicine and e-Health. 7 p.

    Research output: Contribution to journalJournal articleResearchpeer-review

  5. Published

    Transfer learning identifies sequence determinants of cell-type specific regulatory element accessibility

    Salvatore, Marco, Horlacher, M., Marsico, A., Winther, Ole & Andersson, Robin, 2023, In: NAR Genomics and Bioinformatics. 5, 2, 10 p., 026.

    Research output: Contribution to journalJournal articleResearchpeer-review

  6. 2022
  7. 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

  8. 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

  9. 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

  10. 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

  11. 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

  12. 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 paperPreprint

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