RNAGlib Official Documentation

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

Core Features

• Quick access to all available RNA 3D structures with annotations

• Rich functionality for 2.5D RNA graphs, point clouds, and voxels

• RNA graph visualization

• Machine Learning benchmarking tasks

Get started with RNAGlib

• Install

• Quickstart

• Learn about RNA 2.5D Graphs

• Annotation reference

Tutorials

• Working with 2.5D graphs datasets

• Training machine learning models

Package Structure

• rnaglib.prepare_data: processes raw PDB structures and builds a database of 2.5D graphs with full structural annotation

• rnaglib.data_loading: custom PyTorch dataloader and dataset implementations

• rnaglib.representations: graph, voxel, point cloud representations

• rnaglib.learning: learning routines and pre-built GCN models for the easiest use of the package.

• rnaglib.drawing: utilities for visualizing 2.5D graphs

• rnaglib.ged: custom graph similarity functions

• rnaglib.kernels: custom local neighbourhood similarity functions

Source Code and Contact

• RNAglib homepage.

• Source Code.

• Contact rnaglib@cs.mcgill.ca

Associated Repositories

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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

1. 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

Indices and tables

• Index

• Module Index

• Search Page