Current limitations in predicting mRNA translation with deep learning models.

Journal: Genome biology
Published Date:

Abstract

BACKGROUND: The design of nucleotide sequences with defined properties is a long-standing problem in bioengineering. An important application is protein expression, be it in the context of research or the production of mRNA vaccines. The rate of protein synthesis depends on the 5' untranslated region (5'UTR) of the mRNAs, and recently, deep learning models were proposed to predict the translation output of mRNAs from the 5'UTR sequence. At the same time, large data sets of endogenous and reporter mRNA translation have become available.

Authors

  • Niels Schlusser
    Biozentrum, University of Basel, Spitalstrasse 41, 4056, Basel, Switzerland. niels.schlusser@unibas.ch.
  • Asier González
    Biozentrum, University of Basel, Spitalstrasse 41, 4056, Basel, Switzerland.
  • Muskan Pandey
    Biozentrum, University of Basel, Spitalstrasse 41, 4056, Basel, Switzerland.
  • Mihaela Zavolan
    Biozentrum, University of Basel, Spitalstrasse 41, 4056, Basel, Switzerland. mihaela.zavolan@unibas.ch.