Ole Winther

Ole Winther

Professor with special responsibilities, Professor MSO

Member of:

    ORCID: 0000-0002-1966-3205

    Publication year:
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    1 - 10 out of 69Page size: 10
    1. 2023
    2. 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 journal › Journal article › peer-review

    3. 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 journal › Journal article › peer-review

    4. 2022
    5. 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 journal › Journal article › peer-review

    6. 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 journal › Journal article › peer-review

    7. 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 journal › Journal article › peer-review

    8. 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 journal › Journal article › peer-review

    9. 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 journal › Comment/debate

    10. 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 paper › Preprint › Research

    11. 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 journal › Journal article › peer-review

    12. 2021
    13. Published

      A comparison of tools for copy-number variation detection in germline whole exome and whole genome sequencing data

      Gabrielaite, M., Torp, M., Rasmussen, M., Andreu-Sánchez, S., Vieira, Filipe Garrett, Pedersen, C., Kinalis, S., Madsen, M., Yde, C., Rønn, O. L., Marvig, R., Østrup, O., Rossing, Caroline Maria, Nielsen, Finn Cilius, Winther, Ole & Bagger, F. O., 2021, bioRxiv, 29 p.

      Research output: Working paper › Preprint › Research

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    ID: 171145930