OpenFEPOPS: A Python implementation of the FEPOPS molecular similarity technique

Jupyter Notebook Python Submitted 06 August 2023Published 09 November 2023
Review

Editor: @richardjgowers (all papers)
Reviewers: @hannahbaumann (all reviews), @exs-cbouy (all reviews)

Authors

Yan-Kai Chen (0000-0001-7161-9503), Douglas R. Houston (0000-0002-3469-1546), Manfred Auer (0000-0001-8920-3522), Steven Shave (0000-0001-6996-3663)

Citation

Chen et al., (2023). OpenFEPOPS: A Python implementation of the FEPOPS molecular similarity technique. Journal of Open Source Software, 8(91), 5763, https://doi.org/10.21105/joss.05763

@article{Chen2023, doi = {10.21105/joss.05763}, url = {https://doi.org/10.21105/joss.05763}, year = {2023}, publisher = {The Open Journal}, volume = {8}, number = {91}, pages = {5763}, author = {Yan-Kai Chen and Douglas R. Houston and Manfred Auer and Steven Shave}, title = {OpenFEPOPS: A Python implementation of the FEPOPS molecular similarity technique}, journal = {Journal of Open Source Software} }
Copy citation string · Copy BibTeX  
Tags

molecular similarity virtual screening pharmacophores feature points

Altmetrics
Markdown badge

 

License

Authors of JOSS papers retain copyright.

This work is licensed under a Creative Commons Attribution 4.0 International License.

Creative Commons License

Table of Contents
Public user content licensed CC BY 4.0 unless otherwise specified.
ISSN 2475-9066