Deep learning for elucidating modifications to rna—status and challenges ahead

HIGHLIGHTS

• What: Whilst the main focus is on the prediction of mRNA-RBP binding_sites, the authors also highlight publications on other modifications, particularly m6 A and A-to-I editing. The authors focus on supervised approaches here, but other types of models are also extremely useful in biology, such as unsupervised learning of cell clusters from single-cell RNA-sequencing or semi-supervised deep learning for biological imaging analysis , just to name two applications. The majority of these models focus on predicted RNA secondary_structures via the application of computational tools (e_g, RNAfold or RNAshapes . The integration of deep . . .
  

   

  

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