A Custom Jupyter Lab Widget to visualize SMILES-based and atom-based scores.
If you use XSMILES, the use cases, its code, or the generated explanations, please cite our article:
https://jcheminf.biomedcentral.com/articles/10.1186/s13321-022-00673-w
Heberle, H., Zhao, L., Schmidt, S. et al. XSMILES: interactive visualization for molecules, SMILES and XAI attribution scores. J Cheminform 15, 2 (2023). https://doi.org/10.1186/s13321-022-00673-w
@article{Heberle2023XSMILES,
author={Heberle, Henry and Zhao, Linlin and Schmidt, Sebastian and Wolf, Thomas and Heinrich, Julian},
title={XSMILES: interactive visualization for molecules, SMILES and XAI attribution scores},
journal={Journal of Cheminformatics},
year={2023},
month={Jan},
day={06},
volume={15},
number={1},
pages={2},
abstract={Explainable artificial intelligence (XAI) methods have shown increasing applicability in chemistry. In this context, visualization techniques can highlight regions of a molecule to reveal their influence over a predicted property. For this purpose, some XAI techniques calculate attribution scores associated with tokens of SMILES strings or with atoms of a molecule. While an association of a score with an atom can be directly visually represented on a molecule diagram, scores computed for SMILES non-atom tokens cannot. For instance, a substring [N+] contains 3 non-atom tokens, i.e., [, {\$}{\$}+{\$}{\$}, and ], and their attributions, depending on the model, are not necessarily revealing an influence of the nitrogen atom over the predicted property; for that reason, it is not possible to represent the scores on a molecule diagram. Moreover, SMILES's notation is complex, foregrounding the need for techniques to facilitate the analysis of explanations associated with their tokens.},
issn={1758-2946},
doi={10.1186/s13321-022-00673-w},
url={https://doi.org/10.1186/s13321-022-00673-w}
}
To use XSMILES with Jupyter Lab you need to install the package with pip and have internet connection while using it.
RDKit MinimalLib is downloaded by your browser.
Please check this notebook to see how to use the tool: Notebook
Note that it is only being tested with JupyterLab. A reason for you to use Lab is the space available for visualizations, which is much better than in regular Jupyter notebooks. We also had problems with the installation for non-Lab notebooks.
conda create --name xsmiles_env python=3.9 jupyterlab=3.4.5 rdkit=2022.3.5 matplotlib=3.5.3 -c conda-forge
conda activate xsmiles_env # activate the created env
# You can install the latest official version from this repo with:
# pip install xsmiles-0.2.2-py2.py3-none-any.whl
# Unofficial pypi xsmiles:
pip install xsmiles
jupyter lab examples/xsmiles_examples.ipynb # run a notebook with jupyter lab# tested with python 3.9
python3.9 -m venv xsmiles_env
# activate env
source ./xsmiles_env/bin/activate
# You can install the latest official version from this repo with:
# pip install xsmiles-0.2.2-py2.py3-none-any.whl
# Unofficial pypi xsmiles:
pip install xsmiles
# install dependencies for the example notebook
pip install jupyterlab==3.4.5 rdkit==2022.3.5 matplotlib==3.5.3
jupyter lab examples/xsmiles_examples.ipynbpip uninstall xsmilesrm -r <path-to:>/share/jupyter/labextensions/xsmilesjupyter labextension list
Please check the DEVELOPMENT.md file.