Physics-based molecular fingerprints from spectral graph theory provide efficient geometry-aware measures of chemical similarity.

Toney JW, Farnood AY, Darouich S, Kulik HJ

DOI: 10.1039/d6sc06309h
Published: 2026 Oct 15
Container: Chemical science
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.1039/d6sc06309h,
  title = {Physics-based molecular fingerprints from spectral graph theory provide efficient geometry-aware measures of chemical similarity.},
  author = {Toney JW and Farnood AY and Darouich S and Kulik HJ},
  year = {2026},
  journal = {Chemical science},
  doi = {10.1039/d6sc06309h},
  url = {https://doi.org/10.1039/d6sc06309h}
}

RIS

TY  - JOUR
TI  - Physics-based molecular fingerprints from spectral graph theory provide efficient geometry-aware measures of chemical similarity.
AU  - Toney JW
AU  - Farnood AY
AU  - Darouich S
AU  - Kulik HJ
PY  - 2026
JO  - Chemical science
DO  - 10.1039/d6sc06309h
UR  - https://doi.org/10.1039/d6sc06309h
ER  -

APA

JW, T., AY, F., S, D., & HJ, K. (2026). Physics-based molecular fingerprints from spectral graph theory provide efficient geometry-aware measures of chemical similarity.. Chemical science. https://doi.org/10.1039/d6sc06309h

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pubmed · retrieved 2026-11-10T08:44:35.272Z