# 3D-based RNA function prediction tools in rnaglib

arXiv: https://arxiv.org/abs/2402.09330 · HTML: https://mlsanity.com/paper/2402.09330/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 2 of its 12 references that are in the map.
- First posted on arXiv 14 Feb 2024.

## Builds on (most cited first, 2 of 2)

- [Representation Learning on Graphs: Methods and Applications](https://mlsanity.com/paper/1709.05584/) (2017)
- [VeRNAl: Mining RNA Structures for Fuzzy Base Pairing Network Motifs](https://mlsanity.com/paper/2009.00664/) (2020)

## Abstract (arXiv)

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.