MOSES
A benchmarking platform for molecular generation models, providing datasets, implementations, and evaluation metrics for drug discovery research.
What is MOSES?
Molecular Sets (MOSES) is an open-source benchmarking platform for evaluating deep generative models in molecular generation for drug discovery. It provides a standardized dataset, pre-implemented models, and a comprehensive set of metrics to assess the quality, diversity, and novelty of generated molecules. The platform aims to facilitate reproducible research and comparison across different molecular generation approaches.
Researchers and data scientists working on machine learning for drug discovery, particularly those developing or evaluating deep generative models for molecular design. It is also valuable for academic labs and pharmaceutical companies aiming to benchmark their models against established baselines.
MOSES offers a standardized and reproducible framework that eliminates inconsistencies in evaluation, allowing researchers to compare models fairly. Its curated dataset, ready-to-use model implementations, and comprehensive metrics save time and effort, accelerating innovation in computational drug discovery.
Overview
Molecular Sets (MOSES): A Benchmarking Platform for Molecular Generation Models
Use Cases
Best For
- Benchmarking new molecular generation models against established baselines
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