Ole Winther

Ole Winther

Professor with special responsibilities, Visiting professor, Professor MSO

Member of:

    ORCID: 0000-0002-1966-3205

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    1. 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 journal › Journal article › Research › peer-review

    2. Published

      DeepLoc: prediction of protein subcellular localization using deep learning

      Almagro Armenteros, J. J., Sønderby, C. K., Sønderby, S. K., Nielsen, H. & Winther, Ole, 1 Nov 2017, In: Bioinformatics. 33, 21, p. 3387-3395 9 p.

      Research output: Contribution to journal › Journal article › Research › peer-review

    3. Published

      HemaExplorer: a database of mRNA expression profiles in normal and malignant haematopoiesis

      Bagger, F. O., Rapin, N. P. J., Theilgaard-Mønch, Kim, Kaczkowski, B., Thorén, L. A. M., Jendholm, L. J., Winther, Ole & Porse, Bo Torben, 2013, In: Nucleic Acids Research. 41, Database issue, p. D1034-D1039 6 p.

      Research output: Contribution to journal › Journal article › Research › peer-review

    4. Published

      BloodSpot: a database of gene expression profiles and transcriptional programs for healthy and malignant haematopoiesis

      Bagger, F. O., Sasivarevic, D., Hadi Sohi, S., Laursen, L. G., Pundhir, Sachin, Sønderby, C. K., Winther, Ole, Rapin, N. & Porse, Bo Torben, 4 Jan 2016, In: Nucleic Acids Research. 44, D1, p. D917-24 8 p.

      Research output: Contribution to journal › Journal article › Research › peer-review

    5. 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 journal › Review › Research › peer-review

    6. Published

      Competence classification of cumulus and granulosa cell transcriptome in embryos matched by morphology and female age

      Borup, R., Thuesen, L. L., tcg964, tcg964, Andersen, A. N., Ziebe, S., Winther, Ole & Grøndahl, M. L., 2016, In: P L o S One. 11, 4, p. 1-19 19 p., e0153562.

      Research output: Contribution to journal › Journal article › Research › peer-review

    7. Published

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

      Bryne, J. C., Valen, E., Tang, M. E., Marstrand, T., Winther, Ole, da Piedade, I., Krogh, Anders, Lenhard, B. & Sandelin, Albin Gustav, 2008, In: Nucleic Acids Research. 36, Database issue, p. D102-6

      Research output: Contribution to journal › Journal article › Research › peer-review

    8. Published

      Graph neural network interatomic potential ensembles with calibrated aleatoric and epistemic uncertainty on energy and forces

      Busk, J., Schmidt, M. N., Winther, Ole, Vegge, T. & Jørgensen, P. B., 2023, In: Physical Chemistry Chemical Physics. 25, p. 25828-25837 10 p.

      Research output: Contribution to journal › Journal article › Research › peer-review

    9. 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 › Research › peer-review

    10. Published

      Daily estimates of clinical severity of symptoms in bipolar disorder from smartphone-based self-assessments

      Busk, J., Faurholt-Jepsen, M., Frost, M., Bardram, J. E., Kessing, Lars Vedel & Winther, Ole, 2020, In: Translational Psychiatry. 10, 12 p., 194.

      Research output: Contribution to journal › Journal article › Research › peer-review

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    ID: 171145930