| Official site | https://github.com/Lambard-ML-Team/SMILES-X |
|---|---|
| Openness | ★★★ |
| License |
MIT License |
| Core Developers |
Guillaume Lambard (National Institute for Materials Science) Ekaterina Gracheva (National Institute for Materials Science, University of Tsukuba) |
| Availability |
It is highly recommended to use GPUs rather than CPUs.
is required for GPU use.
|
SMILES-X
SMILES-X is an automated pipeline that uses only molecular SMILES as input to predict physicochemical properties, such as solubility, hydration-free energy, and lipophilicity. This tool is specifically designed for small datasets (less than 1000 samples) and doesn’t require human-made descriptors. With it, users can design neural architectures through Bayesian optimization, predict molecular characteristics from a list of SMILES based on these models, and visualize elements or substructures to understand the predictions better.
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