ArticlemSphere2023
STrack: A Tool to Simply Track Bacterial Cells in Microscopy Time-Lapse Images.
Article in mSphere, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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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
5 citing papers in PubMed, 9 citations in OpenAlex.
- Article
- Limits to the evolution of metabolic dependency in spatially structured microbial communities.iScience · 2026Article
- Engineering non-exponential proliferation in Escherichia coli using functionalized protein aggregates.Nature communications · 2026Article
- TrackRefiner a tool for refinement of bacillus cell tracking data.NPJ systems biology and applications · 2025Article
- Droplet microfluidics for single-cell studies: a frontier in ecological understanding of microbiomes.FEMS microbiology reviews · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
Bacterial growth can be studied at the single cell level through time-lapse microscopy imaging. Technical advances in microscopy lead to increasing image quality, which in turn allows to visualize larger areas of growth, containing more and more cells. In this context, the use of automated computational tools becomes essential. In this paper, we present STrack, a tool that allows to track cells in time-lapse images in a fast and efficient way. We compared it to 3 recently published tracking tools on images ranging over 6 different bacterial strains with various morphologies. STrack showed to be the most consistent tracking tool, returning more than 80% of correct cell lineages on average, in comparison to manually annotated ground-truth. The python implementation of STrack, a docker structure, and a tutorial on how to download and use the tool can be found on the following github page: https://github.com/Helena-todd/STrack.
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Identifiers
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.