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