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3D-Based RNA Function Prediction Tools in rnaglib.
Oliver, Carlos; Mallet, Vincent; Waldispühl, Jérôme.
Affiliation
  • Oliver C; Department of Machine Learning and Systems Biology, Max Planck Institute of Biochemistry, Martinsried, Germany. oliver@biochem.mpg.de.
  • Mallet V; LIX, École Polytechnique, Paris, France.
  • Waldispühl J; School of Computer Science, McGill University, Montréal, QC, Canada.
Methods Mol Biol ; 2847: 153-161, 2025.
Article in En | MEDLINE | ID: mdl-39312142
ABSTRACT
Understanding the connection between complex structural features of RNA and biological function is a fundamental challenge in evolutionary studies and in RNA design. However, building datasets of RNA 3D structures and making appropriate modeling choices remain time-consuming and lack standardization. In this chapter, we describe the use of rnaglib, to train supervised and unsupervised machine learning-based function prediction models on datasets of RNA 3D structures.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Software / RNA / Computational Biology / Nucleic Acid Conformation Language: En Journal: Methods Mol Biol Journal subject: BIOLOGIA MOLECULAR Year: 2025 Document type: Article Affiliation country: Germany Country of publication: United States

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Software / RNA / Computational Biology / Nucleic Acid Conformation Language: En Journal: Methods Mol Biol Journal subject: BIOLOGIA MOLECULAR Year: 2025 Document type: Article Affiliation country: Germany Country of publication: United States