Exploring generative deep learning for omics data using log-linear models.

Journal: Bioinformatics (Oxford, England)
Published Date:

Abstract

MOTIVATION: Following many successful applications to image data, deep learning is now also increasingly considered for omics data. In particular, generative deep learning not only provides competitive prediction performance, but also allows for uncovering structure by generating synthetic samples. However, exploration and visualization is not as straightforward as with image applications.

Authors

  • Moritz Hess
    Institute of Medical Biostatistics, Epidemiology and Informatics (IMBEI), University Medical Center, 55131 Mainz, Germany.
  • Maren Hackenberg
    Institute of Medical Biometry and Statistics, Faculty of Medicine and Medical Center - University of Freiburg, 79104 Freiburg, Germany.
  • Harald Binder
    Institute of Medical Biostatistics, Epidemiology and Informatics (IMBEI), University Medical Center, 55131 Mainz, Germany.