Ole Winther

Ole Winther

Professor with special responsibilities, Visiting professor, Professor MSO


  1. 2020
  2. Published

    Identification and validation of 174 COVID-19 vaccine candidate epitopes reveals low performance of common epitope prediction tools

    Prachar, Marek, Justesen, S., Steen-Jensen, D. B., Thorgrimsen, S., Jurgons, E., Winther, Ole & Bagger, F. O., 2020, In: Scientific Reports. 10, 8 p., 20465.

    Research output: Contribution to journalJournal articleResearchpeer-review

  3. Published

    Optimal Variance Control of the Score-Function Gradient Estimator for Importance Weighted Bounds

    Liévin, V., Dittadi, A., Christensen, Anders & Winther, Ole, 2020, In: Advances in Neural Information Processing Systems. 2020-December, 12 p.

    Research output: Contribution to journalConference articleResearchpeer-review

  4. Published

    Systematic review of machine learning for diagnosis and prognosis in dermatology

    Thomsen, K., Iversen, L., Titlestad, T. L. & Winther, Ole, 2020, In: Journal of Dermatological Treatment. 31, 5, p. 496-510

    Research output: Contribution to journalReviewResearchpeer-review

  5. Published

    scVAE: variational auto-encoders for single-cell gene expression data

    Grønbech, Christopher Heje, Vording, M. F., Timshel, P., Sønderby, C. K., Pers, Tune H & Winther, Ole, 2020, In: Bioinformatics. 36, 16, p. 4415-4422 8 p.

    Research output: Contribution to journalJournal articleResearchpeer-review

  6. 2019
  7. Published

    A perspective on inverse design of battery interphases using multi-scale modelling, experiments and generative deep learning

    Bhowmik, A., Castelli, I. E., Garcia-Lastra, J. M., Bjørn-Jørgensen, P., Winther, Ole & Vegge, T., 2019, In: Energy Storage Materials. 21, p. 446-456

    Research output: Contribution to journalReviewResearchpeer-review

  8. Published

    Deconvolution of autoencoders to learn biological regulatory modules from single cell mRNA sequencing data

    Kinalis, S., Nielsen, Finn Cilius, Winther, Ole & Bagger, F. O., 2019, In: BMC Bioinformatics. 20, 9 p., 379.

    Research output: Contribution to journalJournal articleResearchpeer-review

  9. Published

    Detecting sequence signals in targeting peptides using deep learning

    Almagro Armenteros, J. J., Salvatore, Marco, Emanuelsson, O., Winther, Ole, von Heijne, G., Elofsson, A. & Nielsen, H., 2019, In: Life Science Alliance. 2, 5, 14 p., 201900429.

    Research output: Contribution to journalJournal articleResearchpeer-review

  10. Published

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

    Klausen, M. S., Jespersen, M. C., Nielsen, H., Jensen, K. K., Jurtz, V. I., Sønderby, C. K., Sommer, M. O. A., Winther, Ole, Nielsen, M., Petersen, Bent & Marcatili, P., 2019, In: Proteins: Structure, Function and Bioinformatics. 87, 6, p. 520-527

    Research output: Contribution to journalJournal articleResearchpeer-review

  11. 2018
  12. Published

    SinaPlot: an enhanced chart for simple and truthful representation of single observations over multiple classes

    Sidiropoulos, N., Sohi, S. H., Pedersen, T. L., Porse, Bo Torben, Winther, Ole, Rapin, N. & Bagger, F. O., 2018, In: Journal of Computational and Graphical Statistics. 27, 3, p. 673-676 4 p.

    Research output: Contribution to journalJournal articleResearchpeer-review

  13. 2017
  14. Published

    An introduction to deep learning on biological sequence data: examples and solutions

    Jurtz, V. I., Johansen, A. R., Nielsen, M., Almagro Armenteros, J. J., Nielsen, H., Sønderby, C. K., Winther, Ole & Sønderby, S. K., 15 Nov 2017, In: Bioinformatics. 33, 22, p. 3685-3690 6 p.

    Research output: Contribution to journalReviewResearchpeer-review

ID: 171145930