Evidence map›Paper›PMID 29476462›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2018

Image-Based Tracking of Heterogeneous Single-Cell Phenotypes.

Katherin Patsch, Shannon M Mumenthaler, Daniel Ruderman

Abstract read
In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2018. 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

3 authors.

Katherin PatschLawrence J. Ellison Institute for Transformative Medicine, University of Southern California, Los Angeles, CA, USA.
Shannon M MumenthalerLawrence J. Ellison Institute for Transformative Medicine, University of Southern California, Los Angeles, CA, USA.
Daniel RudermanLawrence J. Ellison Institute for Transformative Medicine, University of Southern California, Los Angeles, CA, USA. ruderman@usc.edu.

Funding

USC/NORRIS COMPREHENSIVE CANCER CENTER (CORE) SUPPORTP30CA014089 · NCI · UNIVERSITY OF SOUTHERN CALIFORNIA · PI Fumito Ito · 1985 to 2026
$181.4M
NCI NIH HHS P30 CA014089
6 · The paper itself

Abstract

Cells display broad heterogeneity across multiple phenotypic features, including motility, morphology, and cell signaling. Live-cell imaging techniques are beginning to capture the importance and interdependence of these phenomena. However, existing image analysis pipelines often fail to capture the intricate changes that occur in small subpopulations, either due to poor segmentation protocols or cell tracking errors. Here we report a pipeline designed to image and track single-cell dynamic phenotypes in heterogeneous cell populations. We provide step-by-step instructions for three phenotypically different cell lines across two time scales as well as recommendations for adaptation to custom data sets. Our protocols include steps for quality control that can be used to filter out erroneous tracks and improve assessment of heterogeneity. We demonstrate possible phenotypic readouts including motility, nuclear receptor translocation, and mitosis.

Indexed as

PhenotypeBiomarkersCell LineCell TrackingComputational BiologyGene ExpressionGenes, ReporterHumansImage Processing, Computer-AssistedMicroscopy, FluorescenceMitosisSingle-Cell AnalysisBiomarkersHeterogeneityLive-cell imagingMitosisMotilityPhenotypesReceptor translocationTracking

Identifiers

PMID29476462
PMCPMC8908899

What OpenQuestion holds

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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.