Current limitations in predicting mRNA translation with deep learning models.

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.

Results

In this study, we use complementary data obtained in two different cell types to assess the accuracy and generality of currently available models for predicting translational output. We find that while performing well on the data sets o

SUBMITTER: Schlusser N 

PROVIDER: S-EPMC11337900 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature