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Bioinformatics (Oxford, England)|August 12, 2023
The Deep Generative Decoder: MAP estimation of representations improves modelling of single-cell RNA dataViktoria Schuster, Anders KroghEntropy (Basel, Switzerland)|November 27, 2021
A Manifold Learning Perspective on Representation Learning: Learning Decoder and Representations without an EncoderViktoria Schuster, Anders KroghNature Communications|November 20, 2024
multiDGD: A versatile deep generative model for multi-omics dataViktoria Schuster, Emma Dann, Anders Krogh, et al.Genome Biology|November 17, 2023
N-of-one differential gene expression without control samples using a deep generative modelIñigo Prada-Luengo, Viktoria Schuster, Yuhu Liang, et al.Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics|November 5, 2004
Teaching computers to fold proteinsOle Winther, Anders KroghBMC Genomics|September 15, 2005
Computational evidence for hundreds of non-conserved plant microRNAsMorten Lindow, Anders KroghBMC Bioinformatics|May 23, 2006
Automatic generation of gene finders for eukaryotic speciesKasper Munch, Anders KroghBioinformatics (Oxford, England)|October 27, 2005
Large-scale prokaryotic gene prediction and comparison to genome annotationPernille Nielsen, Anders KroghMethods in Molecular Biology (Clifton, N.J.)|December 14, 2007
Hidden Markov Models for prediction of protein featuresChristopher Bystroff, Anders KroghPageof 13