rnaglib Official Documentation¶

rnaglib (RNA Geometric Library) is a Python package for studying models of RNA 3D structures.

Core Features¶

Quick and detailed access to all available RNA 3D structures with annotations
Train and benchmark deep learning models for RNA 3D structure-function tasks
RNA graph visualization
Create fully reproducible custom datasets and tasks

Get started with rnaglib¶

Tutorials¶

Those tutorials are meant to give you on operational overview of the library

Data reference¶

Pages to read to better understand what is our data and how we build it.

A peek under the hood¶

Pages to give you an understanding of the main objects shipping with RNAglib

Package Structure¶

rnaglib.dataset: custom RNA PyTorch dataset implementations
rnaglib.tasks: prediction tasks for ML benchmarking.
rnaglib.transforms: process and modify RNA data
rnaglib.learning: learning routines and pre-built GCN models for the easiest use of the
rnaglib.prepare_data: processes raw PDB structures and builds a database of 2.5D graphs with full structural annotation package.
rnaglib.drawing: utilities for visualizing 2.5D graphs

Source Code and Contact¶

Associated Repositories¶

RNAmigos : a research paper published in Nucleic Acid Research that demonstrates the usefulness of 2.5D graphs for machine learning tasks, exemplified onto the drug discovery application.

VeRNAl : a research paper published in Bioinformatics that uses learnt vector representations of RNA subgraphs to mine structural motifs in RNA.

References¶

Leontis, N. B., & Zirbel, C. L. (2012). Nonredundant 3D Structure Datasets for RNA Knowledge Extraction and Benchmarking. In RNA 3D Structure Analysis and Prediction N. Leontis & E. Westhof (Eds.), (Vol. 27, pp. 281–298). Springer Berlin Heidelberg. doi:10.1007/978-3-642-25740-7\_13