  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 remains time-consuming and lacks 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.
