Research output per year
Research output per year
Personal profile
Short presentation
I am PhD student employed by the bioinformatics software company Qlucore in Lund, Sweden, enrolled at University of Copenhagen, and funded by the Marie Skłodowska-Curie Innovative Training Network “Machine Learning Frontiers in Precision Medicine”.
I develop deep-learning methods to model and visualise biomedical data, in particular single-cell RNA-sequencing gene expression data, to improve the interpretability of the data.
These methods are deep generative methods, in particular variational auto-encoders (VAEs), and I have worked with Gaussian-mixture VAEs, conditional VAEs, hierarchical VAEs, and mixtures of these.
Collaborations and top research areas from the last five years
Recent external collaboration on country/territory level. Dive into details by clicking on the dots or
-
scVAE: variational auto-encoders for single-cell gene expression data
Grønbech, C. H., Vording, M. F., Timshel, P., Sønderby, C. K., Pers, T. H. & Winther, O., 2020, In: Bioinformatics. 36, 16, p. 4415-4422 8 p.Research output: Contribution to journal › Journal article › Research › peer-review
Open Access122 Citations (Scopus) -
Improved metagenome binning and assembly using deep variational autoencoders
Nissen, J. N., Johansen, J., Allesoe, R. L., Sonderby, C. K., Armenteros, J. J. A., Gronbech, C. H., Jensen, L. J., Nielsen, H. B., Petersen, T. N., Winther, O. & Rasmussen, S., 2021, In: Nature Biotechnology. 39, p. 555-560Research output: Contribution to journal › Journal article › Research › peer-review
File223 Citations (Scopus)33 Downloads (Pure) -
Binning microbial genomes using deep learning
Nissen, J. N., Sønderby, C. K., Armenteros, J. J. A., Grønbech, C. H., Nielsen, H. B., Petersen, T. N., Winther, O. & Rasmussen, S., 2018, (bioRxiv).Research output: Working paper › Preprint › Research
File236 Downloads (Pure)