LegNet: a best-in-class deep learning model for short DNA regulatory regions.

Journal: Bioinformatics (Oxford, England)
Published Date: Aug 1, 2023

Abstract

MOTIVATION: The increasing volume of data from high-throughput experiments including parallel reporter assays facilitates the development of complex deep-learning approaches for modeling DNA regulatory grammar.

Authors

  • Dmitry Penzar
    Vavilov Institute of General Genetics, Moscow 119991, Russia.
  • Daria Nogina
    Faculty of Bioengineering and Bioinformatics, Lomonosov Moscow State University, Moscow 119991, Russia.
  • Elizaveta Noskova
    Faculty of Bioengineering and Bioinformatics, Lomonosov Moscow State University, Moscow 119991, Russia.
  • Arsenii Zinkevich
    Vavilov Institute of General Genetics, Moscow 119991, Russia.
  • Georgy Meshcheryakov
    Institute of Protein Research, Pushchino 142290, Russia.
  • Andrey Lando
    Yandex N.V., Moscow 119021, Russia.
  • Abdul Muntakim Rafi
    School of Biomedical Engineering, University of British Columbia, Vancouver, BC V6T 1Z4, Canada.
  • Carl de Boer
    School of Biomedical Engineering, University of British Columbia, Vancouver, BC V6T 1Z4, Canada.
  • Ivan V Kulakovskiy
    Vavilov Institute of General Genetics, Russian Academy of Sciences, Moscow, 119991, Russia; Center for Precision Genome Editing and Genetic Technologies for Biomedicine, Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, Moscow 119991, Russia. Electronic address: ivan.kulakovskiy@gmail.com.

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