Caveats to Deep Learning Approaches to RNA Secondary Structure Prediction

Caveats to Deep Learning Approaches to RNA Secondary Structure Prediction

Machine learning (ML) and in particular deep learning techniques have gained popularity for predicting structures from biopolymer sequences. An interesting case is the prediction of RNA secondary structures, where well established biophysics based methods exist. The accuracy of these classical metho...

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Bibliographic Details
Main Authors: Christoph Flamm , Julia Wielach, Michael T. Wolfinger, Stefan Badelt, Ronny Lorenz, Ivo L. Hofacker
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-07-01
Series:Frontiers in Bioinformatics
Subjects:
RNA secondary structure
dataset biases
deep learning model
biophysical model
folding prediction
Online Access:https://www.frontiersin.org/articles/10.3389/fbinf.2022.835422/full

Internet

https://www.frontiersin.org/articles/10.3389/fbinf.2022.835422/full

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