ArticleeLife2018
A quantitative approach for analyzing the spatio-temporal distribution of 3D intracellular events in fluorescence microscopy.
Article in eLife, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
12 citing papers in PubMed.
- Spatial relationships between vinculin tension and actin at cell adhesions define cell colony positioning and identity.Biophysical journal · 2026Article
- Deep learning detection of dynamic exocytosis events in fluorescence TIRF microscopy.PLoS computational biology · 2025Article
- Article
- Temporal analysis of relative distances (TARDIS) is a robust, parameter-free alternative to single-particle tracking.Nature methods · 2024Article
- Comprehensive and quantitative analysis of intracellular structure polarization at the apical-basal axis in elongating Arabidopsis zygotes.Scientific reports · 2023Article
- Cellular harmonics for the morphology-invariant analysis of molecular organization at the cell surface.Nature computational science · 2023Article
- SPITFIR(e): a supermaneuverable algorithm for fast denoising and deconvolution of 3D fluorescence microscopy images and videos.Scientific reports · 2023Article
- A generative model to simulate spatiotemporal dynamics of biomolecules in cells.Biological imaging · 2023Article
- Human carboxylesterases and fluorescent probes to image their activity in live cells.RSC medicinal chemistry · 2021Review
- Fluorescence lifetime imaging microscopy: fundamentals and advances in instrumentation, analysis, and applications.Journal of biomedical optics · 2020Review
- Particle Mobility Analysis Using Deep Learning and the Moment Scaling Spectrum.Scientific reports · 2019Article
- Cellular Metrology: Scoping for a Value Proposition in Extra- and Intracellular Measurements.Frontiers in bioengineering and biotechnology · 2019Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Analysis of the spatial distribution of endomembrane trafficking is fundamental to understand the mechanisms controlling cellular dynamics, cell homeostasy, and cell interaction with its external environment in normal and pathological situations. We present a semi-parametric framework to quantitatively analyze and visualize the spatio-temporal distribution of intracellular events from different conditions. From the spatial coordinates of intracellular features such as segmented subcellular structures or vesicle trajectories, QuantEv automatically estimates weighted densities that are easy to interpret and performs a comprehensive statistical analysis from distribution distances. We apply this approach to study the spatio-temporal distribution of moving Rab6 fluorescently labeled membranes with respect to their direction of movement in crossbow- and disk-shaped cells. We also investigate the position of the generating hub of Rab11-positive membranes and the effect of actin disruption on Rab11 trafficking in coordination with cell shape.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.