Projects per year
Abstract
Since the advent of stochastic localization microscopy approaches in 2006, the number of studies employing this strategy to investigate the subdiffraction limit features of fluorescently labeled structures in biology, biophysics and solid state samples has increased exponentially. Underpinning all these approaches is the notion that the position of single molecules can be determined to high precision, provided enough photons are collected. The determination of exactly how precisely, has been demanded to formulas that try to approximate the so-called Cramer-Rao lower bound based on input parameters such as the number of photons collected from the molecules, or the size of the camera pixel. These estimates should, however, be matched to the experimental localization precision, which can be easily determined if, instead of looking at single beads, we study the distance between a pair. We revisit here a few key works, observing how these theoretical determinations tend to routinely underestimate the experimental localization precision of the order of a factor 2. A software-independent metric to determine, based on each individual setup, the appropriate value to set on the localization error of individual emitters is provided. [Abstract copyright: Copyright © 2025 The Authors. Published by Elsevier Inc. All rights reserved.]
| Original language | English |
|---|---|
| Article number | 100223 |
| Pages (from-to) | 1-7 |
| Number of pages | 7 |
| Journal | Biophysical Reports |
| Volume | 5 |
| Issue number | 3 |
| Early online date | 24 Jul 2025 |
| DOIs | |
| Publication status | Published - 10 Sept 2025 |
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Dive into the research topics of 'Single-molecule localization microscopy error is sensor dependent and larger than theory predicts'. Together they form a unique fingerprint.Projects
- 1 Active
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Geometry and finesse: Bottom-up nanoscale control of compartmentalized cellular signaling: geometry and finesse
Annibale, P. (PI)
1/05/23 → 30/04/28
Project: Standard
Datasets
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Single-molecule localization microscopy error is sensor dependent and larger than theory predicts (code)
Brenlla-Lopez, A. (Creator), Deen, L. (Creator) & Annibale, P. (Creator), GitHub, 2024
https://github.com/brenlla1/Localisation-precision
Dataset: Software