Bayesian Learning of Distance Metrics Beyond RMSD for Biomolecule Alignment, Clustering, and Domain Identification

Saumyak Mukherjee, Gerhard Hummer

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DOI: 10.1021/acs.jctc.6c01395
Published: 2026-10-01
Container: Journal of Chemical Theory and Computation
Publisher: American Chemical Society (ACS)
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.1021/acs.jctc.6c01395,
  title = {Bayesian Learning
of Distance Metrics Beyond RMSD
for Biomolecule Alignment, Clustering, and Domain Identification},
  author = {Saumyak Mukherjee and Gerhard Hummer},
  year = {2026},
  journal = {Journal of Chemical Theory
and Computation},
  doi = {10.1021/acs.jctc.6c01395},
  url = {https://doi.org/10.1021/acs.jctc.6c01395}
}

RIS

TY  - JOUR
TI  - Bayesian Learning
of Distance Metrics Beyond RMSD
for Biomolecule Alignment, Clustering, and Domain Identification
AU  - Saumyak Mukherjee
AU  - Gerhard Hummer
PY  - 2026
JO  - Journal of Chemical Theory
and Computation
DO  - 10.1021/acs.jctc.6c01395
UR  - https://doi.org/10.1021/acs.jctc.6c01395
ER  -

APA

Mukherjee, S., & Hummer, G. (2026). Bayesian Learning of Distance Metrics Beyond RMSD for Biomolecule Alignment, Clustering, and Domain Identification. Journal of Chemical Theory and Computation. https://doi.org/10.1021/acs.jctc.6c01395

Source records

crossref · retrieved 2026-11-05T10:39:37.063Z