ArticleeLife2019
Motion sensing superpixels (MOSES) is a systematic computational framework to quantify and discover cellular motion phenotypes.
Article in eLife, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 11 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.
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Who cites it
11 citing papers in PubMed, 18 citations in OpenAlex.
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- RhoU forms homo-oligomers to regulate cellular responses.Journal of cell science · 2024Article
- Unsupervised Contour Tracking of Live Cells by Mechanical and Cycle Consistency Losses.Proceedings. IEEE Computer Society Conference on Computer Vision and Pattern Recognition · 2023Article
- Surface-guided computing to analyze subcellular morphology and membrane-associated signals in 3D.bioRxiv : the preprint server for biology · 2023Article
- Surface-guided computing to analyze subcellular morphology and membrane-associated signals in 3D.ArXiv · 2023Article
- Emerging machine learning approaches to phenotyping cellular motility and morphodynamics.Physical biology · 2021Review
- Visualization of T Cell Migration in the Spleen Reveals a Network of Perivascular Pathways that Guide Entry into T Zones.Immunity · 2020Article
- DeepScratch: Single-cell based topological metrics of scratch wound assays.Computational and structural biotechnology journal · 2020Article
- Characterization of Biological Motion Using Motion Sensing Superpixels.Bio-protocol · 2019Article
- Characterization of the Dynamic Behavior of Neutrophils Following Influenza Vaccination.Frontiers in immunology · 2019Article
Corrections and comments
- Erratum issued
Authors and funding
6 authors at 1 institution in 1 country.
Funding
Abstract
Correct cell/cell interactions and motion dynamics are fundamental in tissue homeostasis, and defects in these cellular processes cause diseases. Therefore, there is strong interest in identifying factors, including drug candidates that affect cell/cell interactions and motion dynamics. However, existing quantitative tools for systematically interrogating complex motion phenotypes in timelapse datasets are limited. We present Motion Sensing Superpixels (MOSES), a computational framework that measures and characterises biological motion with a unique superpixel 'mesh' formulation. Using published datasets, MOSES demonstrates single-cell tracking capability and more advanced population quantification than Particle Image Velocimetry approaches. From > 190 co-culture videos, MOSES motion-mapped the interactions between human esophageal squamous epithelial and columnar cells mimicking the esophageal squamous-columnar junction, a site where Barrett's esophagus and esophageal adenocarcinoma often arise clinically. MOSES is a powerful tool that will facilitate unbiased, systematic analysis of cellular dynamics from high-content time-lapse imaging screens with little prior knowledge and few assumptions.
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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.