Startseite Challenges for machine learning in RNA-protein interaction prediction
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Challenges for machine learning in RNA-protein interaction prediction

  • Viplove Arora ORCID logo und Guido Sanguinetti EMAIL logo
Veröffentlicht/Copyright: 2. Mai 2022

Abstract

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.


Corresponding author: Guido Sanguinetti, Data Science, Department of Physics, International School for Advanced Studies (SISSA), Trieste 34136, Italy, E-mail:

  1. Author contribution: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.

  2. Research funding: None declared.

  3. Conflict of interest statement: The authors declare no conflicts of interest regarding this article.

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Received: 2021-12-10
Accepted: 2022-01-02
Published Online: 2022-05-02

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