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¶
Tutorials¶
Package Structure¶
rnaglib.data_loading: custom PyTorch dataloader and 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¶
Contact rnaglib@cs.mcgill.ca
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