DeepLoc: prediction of protein subcellular localization using deep learning.

Journal: Bioinformatics (Oxford, England)
Published Date:

Abstract

MOTIVATION: The prediction of eukaryotic protein subcellular localization is a well-studied topic in bioinformatics due to its relevance in proteomics research. Many machine learning methods have been successfully applied in this task, but in most of them, predictions rely on annotation of homologues from knowledge databases. For novel proteins where no annotated homologues exist, and for predicting the effects of sequence variants, it is desirable to have methods for predicting protein properties from sequence information only.

Authors

  • José Juan Almagro Armenteros
    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.
  • Søren Kaae Sønderby
    The Bioinformatics Centre, Department of Biology, University of Copenhagen, 2200 Copenhagen N, Denmark.
  • Henrik Nielsen
    Department of Bio and Health Informatics, Technical University of Denmark, 2800 Kgs. Lyngby, Denmark.
  • Ole Winther
    The Bioinformatics Centre, Department of Biology, University of Copenhagen, 2200 Copenhagen N, Denmark.