natelgrw/ReTiNA

⚗️ ReTiNA: A Benchmark Dataset for LC-MS Retention Time Modeling

ReTiNA is a large open-source dataset for training machine learning models to predict small molecule retention times in LC-MS workflows.

Available models trained on the ReTiNA dataset are available at this Hugging Face Repository.

Source code for the ReTiNA model collection is available at this Github Repository.

This dataset is actively expanding with new experimental retention time values from the Coley Research Group at MIT, ensuring it remains a growing resource for optical property prediction.

ReTiNA is designed for use in:

• Estimating retention times for new compound–environment combinations
• Aiding in peak assignment during LC-MS method development
• Training ML models for retention time prediction under specific conditions

📈 The ReTiNA Dataset

The ReTiNA dataset contains:

• 119,039 unique molecule–environment combinations, the largest singular LC-MS retention time dataset of its kind to date
• Experimentally measured retention times, in seconds, curated from public datasets, benchmark papers, and literature
• Chemical descriptors for 105,809 unique compounds, 6 unique solvents, and 8 unique additives

73 distinct LC-MS setup environments are used in ReTiNA. Each environment consists of:

• Solvent mixtures A and B, consisting of solvents and solvent additives contributing to pH
• The mobile phase gradient used, defined by the percentage of solvent mixture B over time (min)
• The chromatographic technique used - either HILIC or reverse phase
• LC-MS column dimensions, in terms of column length (mm), internal diameter (mm), and particle size (µm)
• The mobile phase flow rate, measured in mL/min
• The column temperature, measured in degrees Celsius

The ReTiNA dataset is divided into different scaffold, cluster, and method splits, which can be accessed in the data directory and are using in model evaluation.

📋 Data Sources Used

Detailed information on the data sources comprising ReTiNA can be found in the data folder.

✒️ Citation

If you use this code in a project, please cite the following:

@dataset{retinadataset,
  title={ReTiNA: A Benchmark Dataset for LC-MS Retention Time Modeling},
  author={Leung, Nathan},
  institution={Coley Research Group @ MIT}
  year={2025},
  howpublished={\url{https://huggingface.co/datasets/natelgrw/ReTiNA}}
}