---
title: Flare
emoji: 🔥 
colorFrom: green
colorTo: blue
sdk: streamlit
pinned: false
python_version: 3.11.7
---

# 🔥 FLARE
Fine-grained Learning for Aligment of spectra-molecule REpresentation

### Authors  
**Yan Zhou Chen, Soha Hassoun**  
Department of Computer Science, Tufts University  

---

FLARE is a framework for **ranking molecular candidates given a mass spectrum**. Beyond candidate ranking, FLARE provides **visualization of peak-to-node attribution**, enabling deeper insights into how spectral peaks correspond to molecular graph nodes.

---

## 🌐 Visualize Peak-to-Node Correspondence
Explore our interactive [app](https://huggingface.co/spaces/HassounLab/FLARE) to visualize peak-to-node attributes in real time.

---
## 🛠 Set up
### Clone repository
```
git clone https://huggingface.co/spaces/HassounLab/FLARE
cd flare
```
### Set up environment and install dependencies
```
conda create -n flare python=3.11
conda activate flare
pip install -r requirements.txt
```
---
## 🚀 Usage
Modify params.yaml as necessary

```
# preprocess data
python subformula_assign/assign_subformulae.py --spec-files ../data/sample/data.tsv --output-dir ../data/sample/subformulae --labels-file ../data/sample/data.tsv --max-formulae 60

# train 
python train.py

# test
python test.py
```

---
## 🙏 Acknowledgments
- **Training Data**: [MassSpecGym](https://github.com/pluskal-lab/MassSpecGym)
- **Subformula Assigner Code**: [MIST](https://github.com/samgoldman97/mist/tree/main_v2)

---
## 📧 Contact
For questions, reach out to soha.hassoun@tufts.edu