Update README.md

README.md

@@ -1,3 +1,112 @@
----
-license: mit
----
+---
+license: mit
+tags:
+- rna
+- biology
+- rna-design
+- biomolecule-design
+- 3d-design
+- inverse-folding
+- inverse-design
+---
+
+# gRNAde Datasets
+
+[![BioRxiv](https://img.shields.io/badge/bioRxiv-2025.11.29-b31b1b.svg)](https://www.biorxiv.org/content/10.1101/2025.11.29.691298)
+[![License](https://img.shields.io/badge/License-MIT-blue.svg)](https://github.com/chaitjo/geometric-rna-design/blob/main/LICENSE)
+[![GitHub](https://img.shields.io/badge/GitHub-Repository-black)](https://github.com/chaitjo/geometric-rna-design)
+
+This repository contains datasets and wet-lab experimental data for **gRNAde**, a generative AI framework for RNA inverse design.
+
+![gRNAde pipeline](https://raw.githubusercontent.com/chaitjo/geometric-rna-design/refs/heads/main/gRNAde_pipeline.jpg)
+
+## 📦 Datasets and Experimental Data
+
+```
+.
+├── RNASolo_31102023_processed.pt       # Pre-processed training dataset (ready for ML)
+├── RNASolo_31102023_raw.tar.gz         # Raw PDB structures from RNASolo
+└── projects                            # Data for reproducing design campaigns in the paper
+    ├── openknot_benchmark              # Eterna OpenKnot Benchmark for psuedoknotted RNA design
+    └── rna_polymerase_ribozyme         # Generative Design of RNA polymerase ribozymes
+```
+
+### Pre-processed Training Dataset
+- **File**: `RNASolo_31102023_processed.pt`
+- **Description**: ML-ready dataset of RNA 3D structures from the Protein Data Bank
+- **Source**: RNASolo database (October 31, 2023 cutoff)
+- **Resolution**: ≤4.0 Å
+- **Format**: PyTorch tensors with sequences, 3D coordinates, secondary structures, and metadata
+- **Use case**: Training new gRNAde models or fine-tuning for specific RNA families
+
+### Raw PDB Structures
+- **File**: `RNASolo_31102023_raw.tar.gz`
+- **Description**: Raw PDB files for all RNA structures from RNASolo
+- **Contents**: Thousands of experimentally determined RNA structures
+- **Use case**: Custom data processing pipelines or structure visualization
+
+### Eterna OpenKnot Competition Data
+- **Directory**: `projects/openknot_benchmark/`
+- **Description**: Designs and experimental validation data from the Eterna OpenKnot Benchmark
+- **Contents**: Chemical probing data, OpenKnot scores, and designed sequences
+- **Targets**: 40 pseudoknotted RNA puzzles including riboswitches, ribozymes, and viral elements
+
+### RNA Polymerase Ribozyme Data
+- **Directory**: `projects/rna_polymerase_ribozyme/`
+- **Description**: Functional design campaign data for engineering RNA polymerase ribozymes
+- **Contents**: Generated sequences, activity assays, fitness landscapes
+
+## 🚀 Quick Start
+
+After setting up the [gRNAde codebase](https://github.com/chaitjo/geometric-rna-design), datasets can be downloaded manually or using HuggingFace CLI (recommended):
+
+```bash
+# Ensure you are in the base directory
+cd ~/geometric-rna-design
+
+# Install HuggingFace CLI (https://huggingface.co/docs/huggingface_hub/main/en/guides/cli)
+pip install -U "huggingface_hub[cli]"
+# alternate: curl -LsSf https://hf.co/cli/install.sh | bash
+# alternate: brew install huggingface-cli
+
+# Download all datasets to data/ directory
+huggingface-cli download chaitjo/gRNAde_datasets --local-dir data/ --repo-type dataset
+```
+
+Alternately, download specific files:
+
+```bash
+# Download only the pre-processed training dataset
+huggingface-cli download chaitjo/gRNAde_datasets RNASolo_31102023_processed.pt --local-dir data/ --repo-type dataset
+
+# Download only raw PDB structures
+huggingface-cli download chaitjo/gRNAde_datasets RNASolo_31102023_raw.tar.gz --local-dir data/ --repo-type dataset
+```
+
+## Citations
+
+```
+@article{joshi2025generative,
+  title={Generative inverse design of RNA structure and function with g{RNA}de},
+  author={Joshi, Chaitanya K and Gianni, Edoardo and Kwok, Samantha LY and Mathis, Simon V and Lio, Pietro and Holliger, Philipp},
+  journal={bioRxiv},
+  year={2025},
+  publisher={Cold Spring Harbor Laboratory}
+}
+
+@inproceedings{joshi2025grnade,
+  title={g{RNA}de: Geometric Deep Learning for 3D RNA inverse design},
+  author={Joshi, Chaitanya K and Jamasb, Arian R and Vi{\~n}as, Ramon and Harris, Charles and Mathis, Simon V and Morehead, Alex and Anand, Rishabh and Li{\`o}, Pietro},
+  booktitle={International Conference on Learning Representations (ICLR)},
+  year={2025},
+}
+
+@incollection{joshi2024grnade,
+  title={g{RNA}de: A Geometric Deep Learning pipeline for 3D RNA inverse design},
+  author={Joshi, Chaitanya K and Li{\`o}, Pietro},
+  booktitle={RNA Design: Methods and Protocols},
+  pages={121--135},
+  year={2024},
+  publisher={Springer}
+}
+```