Evidence map›Paper›PMID 41249144›Full record

ArticleNPJ systems biology and applications2025

TrackRefiner a tool for refinement of bacillus cell tracking data.

Atiyeh Ahmadi, Alireza Dostmohammadi, Rhyan Mclean, Brian Ingalls

Abstract read
In one paragraph

Article in NPJ systems biology and applications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Atiyeh AhmadiBiology, University of Waterloo, Ontario, Canada.
Alireza DostmohammadiBioinformatics and Computational Biophysics, University of Duisburg-Essen, Essen, Germany.
Rhyan McleanBiology, University of Waterloo, Ontario, Canada.
Brian IngallsApplied Mathematics, University of Waterloo, Ontario, Canada. bingalls@uwaterloo.ca.

Funding

Natural Sciences and Engineering Research Council of Canada RGPIN-03826-2018
6 · The paper itself

Abstract

Single-cell resolution time-lapse microscopy of bacterial populations is a powerful tool for assessing cellular behavior and interaction dynamics. Realizing its full potential requires accurate image analysis: segmentation of individual cell objects, tracking of persistent cells from frame to frame, and connecting of mother cells to daughters during division events. Tracking is particularly challenging in densely packed populations or when cells move significantly; Leading software often struggles. To address this, we present TrackRefiner, a tool for refinement of bacillus cell tracking data. This package was specifically designed to refine the tracking outputs of CellProfiler. Benchmarks involve non-motile, rod-shaped bacteria; extension to motile species or other morphologies remains to be demonstrated. For timelapses with frequent imaging, TrackRefiner achieved-with one exception-over 98% detection accuracy and corrected 57-100% of tracking errors. TrackRefiner is published on PyPI and Anaconda . Source code, user manuals, and the benchmark dataset are available on Github and OSF .

Indexed as

BacillusCell TrackingImage Processing, Computer-AssistedSoftwareAlgorithmsSingle-Cell AnalysisTime-Lapse Imaging

Identifiers

PMID41249144
PMCPMC12624007

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.