Evidence map›Paper›PMID 23520484›Full record

ArticlePloS one2013

An algorithm to automate yeast segmentation and tracking.

Andreas Doncic, Umut Eser, Oguzhan Atay, Jan M Skotheim

Abstract read
In one paragraph

Article in PloS one, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers.

0numbers the graph read from it
0cells of the map it votes in
47citing 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

47 citing papers in PubMed.

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  16. Docking to a Basic Helix Promotes Specific Phosphorylation by G1-Cdk1.International journal of molecular sciences · 2021
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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.

Andreas DoncicDepartment of Biology, Stanford University, Stanford, California, United States of America.
Umut Eser
Oguzhan Atay
Jan M Skotheim

Funding

Mechanisms of restriction point response to dynamic growth factor signalsR01GM092925 · NIGMS · STANFORD UNIVERSITY · PI SKOTHEIM, JAN M · 2010 to 2018
$2.8M
NIGMS NIH HHS GM092925NIGMS NIH HHS R01 GM092925
6 · The paper itself

Abstract

Our understanding of dynamic cellular processes has been greatly enhanced by rapid advances in quantitative fluorescence microscopy. Imaging single cells has emphasized the prevalence of phenomena that can be difficult to infer from population measurements, such as all-or-none cellular decisions, cell-to-cell variability, and oscillations. Examination of these phenomena requires segmenting and tracking individual cells over long periods of time. However, accurate segmentation and tracking of cells is difficult and is often the rate-limiting step in an experimental pipeline. Here, we present an algorithm that accomplishes fully automated segmentation and tracking of budding yeast cells within growing colonies. The algorithm incorporates prior information of yeast-specific traits, such as immobility and growth rate, to segment an image using a set of threshold values rather than one specific optimized threshold. Results from the entire set of thresholds are then used to perform a robust final segmentation.

Indexed as

AlgorithmsCell DivisionImage Processing, Computer-AssistedMicroscopy, FluorescenceSaccharomyces cerevisiae

Identifiers

PMID23520484
PMCPMC3592893

What OpenQuestion holds

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LicenceCC BY
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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.