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Challenges for machine learning in RNA-protein interaction prediction.

Viplove AroraGuido Sanguinetti
Published in: Statistical applications in genetics and molecular biology (2022)
RNA-protein interactions have long being recognised as crucial regulators of gene expression. Recently, the development of scalable experimental techniques to measure these interactions has revolutionised the field, leading to the production of large-scale datasets which offer both opportunities and challenges for machine learning techniques. In this brief note, we will discuss some of the major stumbling blocks towards the use of machine learning in computational RNA biology, focusing specifically on the problem of predicting RNA-protein interactions from next-generation sequencing data.
Keyphrases
  • machine learning
  • gene expression
  • big data
  • artificial intelligence
  • protein protein
  • amino acid
  • nucleic acid
  • dna methylation
  • binding protein
  • deep learning
  • small molecule
  • rna seq