Publikationer pr. år
Publikationer pr. år
Personlig profil
Kort præsentation
I am a professor in the Department of Computer Science and the head of the Center for Health Data Science (HeaDS) in the Faculty of Health and Medical Sciences. I have a Ph.D. in theoretical physics, but moved into machine learning and bioinformatics during my PhD. I have worked at UCSC, the Sanger Centre in Cambridge and at the Technical University of Denmark before joining the University of Copenhagen in 2002, where I was affiliated with the Department of Biology until 2020. I have worked in many areas of bioinformatics and machine learning, both with theory and applications. I am probably most well-known for my early work on hidden Markov models for biological sequences. In recent years I have focussed on deep generative models and applied them to gene expression data and other bio/medical data.
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Publikation
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N-of-one differential gene expression without control samples using a deep generative model
Prada-Luengo, I., Schuster, V., Liang, Y., Terkelsen, T., Sora, V. & Krogh, A., 2023, I: Genome Biology. 24, 1, 17 s., 263.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › peer review
Åben adgangFil1 Citationer (Scopus)31 Downloads (Pure) -
Synthetic Data Generation by Artificial Intelligence to Accelerate Research and Precision Medicine in Hematology
D'Amico, S., Dall'Olio, D., Sala, C., Dall'Olio, L., Sauta, E., Zampini, M., Asti, G., Lanino, L., Maggioni, G., Campagna, A., Ubezio, M., Russo, A., Bicchieri, M. E., Riva, E., Tentori, C. A., Travaglino, E., Morandini, P., Savevski, V., Santoro, A., Prada-Luengo, I. & 9 flere, , 2023, I: JCO clinical cancer informatics. 7, s. 1-22 e2300021.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › peer review
Åben adgangFil47 Downloads (Pure) -
The Deep Generative Decoder: MAP estimation of representations improves modelling of single-cell RNA data
Schuster, V. & Krogh, A., 2023, I: Bioinformatics. 39, 9, 14 s., btad497.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › peer review
Åben adgangFil2 Citationer (Scopus)23 Downloads (Pure) -
Context dependency of nucleotide probabilities and variants in human DNA
Liang, Y., Grønbæk, C., Fariselli, P. & Krogh, A., 2022, I: BMC Genomics. 23, 1, 15 s., 87.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › peer review
Åben adgangFil3 Citationer (Scopus)61 Downloads (Pure) -
Context dependent prediction in DNA sequence using neural networks
Grønbæk, C., Liang, Y., Elliott, D. & Krogh, A., 2022, I: PeerJ. 10, 22 s., e13666.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › peer review
Åben adgangFil38 Downloads (Pure) -
A manifold learning perspective on representation learning: Learning decoder and representations without an encoder
Schuster, V. & Krogh, A., nov. 2021, I: Entropy. 23, 11, 14 s., 1403.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › peer review
Åben adgangFil2 Citationer (Scopus)47 Downloads (Pure) -
High-throughput proteomics of breast cancer interstitial fluid: identification of tumor subtype-specific serologically relevant biomarkers
Terkelsen, T., Pernemalm, M., Gromov, P., Borresen-Dale, A-L., Krogh, A., Haakensen, V. D., Lethio, J., Papaleo, E. & Gromova, I., 2021, I: Molecular Oncology. 15, 2, s. 429-461 33 s.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › peer review
Åben adgangFil21 Citationer (Scopus)53 Downloads (Pure) -
CAncer bioMarker Prediction Pipeline (CAMPP) - A standardized framework for the analysis of quantitative biological data
Terkelsen, T., Krogh, A. & Papaleo, E., 2020, I: PLOS Computational Biology. 16, 3, 20 s., e1007665.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › peer review
Åben adgangFil12 Citationer (Scopus)126 Downloads (Pure)