This repository provides
- the code to produce all subfigures (generated programmatically), as well as
- the final figures in the review.
The folder image_generation holds the following information:
- ligand_encoding: scripts to produce ligand encoding examples
- complex_encoding: scripts to produce complex encoding examples
- review_images: composed review figures
Check out more of our work at Volkamer Lab.
Create a conda environment:
$ conda env create -f devtools/env.yml
Activate the environment:
$ conda activate dl-review
Install widgets:
(dl-review)$ jupyter labextension install @jupyter-widgets/jupyterlab-manager nglview-js-widgets
Run jupyter lab:
(dl-review)$ jupyter lab
Kimber, Talia B.; Chen, Yonghui; Volkamer, Andrea. 2021. "Deep Learning in Virtual Screening: Recent Applications and Developments" Int. J. Mol. Sci. 22, no. 9: 4435. https://doi.org/10.3390/ijms22094435
@article{doi:10.3390/ijms22094435,
author = {Kimber, Talia B. and Chen, Yonghui and Volkamer, Andrea},
title = {Deep Learning in Virtual Screening: Recent Applications and Developments},
journal = {International Journal of Molecular Sciences},
volume = {22},
year = {2021},
number = {9},
article-number = {4435},
url = {https://www.mdpi.com/1422-0067/22/9/4435},
ISSN = {1422-0067},
doi = {10.3390/ijms22094435}
}