An introduction to deep learning on biological sequence data: examples and solutions.

Journal: Bioinformatics (Oxford, England)
Published Date: Nov 15, 2017

Abstract

MOTIVATION: Deep neural network architectures such as convolutional and long short-term memory networks have become increasingly popular as machine learning tools during the recent years. The availability of greater computational resources, more data, new algorithms for training deep models and easy to use libraries for implementation and training of neural networks are the drivers of this development. The use of deep learning has been especially successful in image recognition; and the development of tools, applications and code examples are in most cases centered within this field rather than within biology.

Authors

  • Vanessa Isabell Jurtz
    Department of Bio and Health Informatics.
  • Alexander Rosenberg Johansen
    Department of Applied Mathematics and Computer Science, Technical University of Denmark, Lyngby, Denmark.
  • Morten Nielsen
    Department of Health Technology, Technical University of Denmark, Lyngby, Denmark.
  • José Juan Almagro Armenteros
    Department of Bio and Health Informatics, Technical University of Denmark, 2800 Kgs. Lyngby, Denmark.
  • Henrik Nielsen
    Department of Bio and Health Informatics, Technical University of Denmark, 2800 Kgs. Lyngby, Denmark.
  • Casper Kaae Sønderby
    The Bioinformatics Centre, Department of Biology, University of Copenhagen, 2200 Copenhagen N, Denmark.
  • Ole Winther
    The Bioinformatics Centre, Department of Biology, University of Copenhagen, 2200 Copenhagen N, Denmark.
  • Søren Kaae Sønderby
    The Bioinformatics Centre, Department of Biology, University of Copenhagen, 2200 Copenhagen N, Denmark.

Keywords

External Resources

Popular Topics
Recent Journals