WikiSysop: Created page with "== Citation == M. L. Chaillet, S. Roet, R. C. Veltkamp, and F. Förster, “pytom-match-pick: a tophat-transform constraint for automated classification in template matching,” J. Structural Biology X, p. 100125, 2025. == Abstract == Template matching (TM) in cryo-electron tomography (cryo-ET) enables in situ detection and localization of known macromolecules. However, TM faces challenges of weak signal of the macromolecules and interfering features with a high signa..."

2025-07-08T07:05:28Z

Created page with "== Citation == M. L. Chaillet, S. Roet, R. C. Veltkamp, and F. Förster, “pytom-match-pick: a tophat-transform constraint for automated classification in template matching,” J. Structural Biology X, p. 100125, 2025. == Abstract == Template matching (TM) in cryo-electron tomography (cryo-ET) enables in situ detection and localization of known macromolecules. However, TM faces challenges of weak signal of the macromolecules and interfering features with a high signa..."

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== Citation ==

M. L. Chaillet, S. Roet, R. C. Veltkamp, and F. Förster, “pytom-match-pick: a tophat-transform constraint for automated classification in template matching,” J. Structural Biology X, p. 100125, 2025.

== Abstract ==

Template matching (TM) in cryo-electron tomography (cryo-ET) enables in situ detection and localization of
known macromolecules. However, TM faces challenges of weak signal of the macromolecules and interfering
features with a high signal-to-noise ratio, which are often addressed by time-consuming, subjective manual
curation of results. To improve the detection performance we introduce pytom-match-pick, a GPU-accelerated,
open-source command line interface for enhanced TM in cryo-ET. Using pytom-match-pick, we first quantify
the effects of point spread function (PSF) weighting and show that a tilt-weighted PSF outperforms a binary
wedge with a single defocus estimate. We also assess previously introduced background normalization methods
for classification performance. This indicates that phase randomization is more effective than spectrum whitening
in reducing false positives. Furthermore, a novel application of the tophat transform on score maps,
combined with a dual-constraint thresholding strategy, reduces false positives and improves precision. We
benchmarked pytom-match-pick on public datasets, demonstrating improved classification and localization of
macromolecules like ribosomal subunits and proteasomes that led to fewer artifacts in subtomogram averages.
This tool promises to advance visual proteomics by improving the efficiency and accuracy of macromolecule
detection in cellular contexts.

== Keywords ==

== Links ==

https://www.sciencedirect.com/science/article/pii/S2590152425000066

== Related software ==

== Related methods ==

== Comments ==

2025Chaillet PytomMatchPick - Revision history