Evidence map›Paper›PMID 35030161›Full record

ArticlePLoS computational biology2022

Computable early Caenorhabditis elegans embryo with a phase field model.

Xiangyu Kuang, Guoye Guan, Ming-Kin Wong, Lu-Yan Chan, Zhongying Zhao, Chao Tang, Lei Zhang

Abstract read
In one paragraph

Article in PLoS computational biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

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  11. Delineating the mechanisms and design principles ofComputational and structural biotechnology journal · 2022
    Review
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

7 authors.

Xiangyu KuangCenter for Quantitative Biology, Peking University, Beijing, China.ORCID 0000-0003-2662-0817
Guoye GuanCenter for Quantitative Biology, Peking University, Beijing, China.ORCID 0000-0003-4479-4722
Ming-Kin WongDepartment of Biology, Hong Kong Baptist University, Hong Kong, China.ORCID 0000-0002-4088-3819
Lu-Yan ChanDepartment of Biology, Hong Kong Baptist University, Hong Kong, China.
Zhongying ZhaoDepartment of Biology, Hong Kong Baptist University, Hong Kong, China.ORCID 0000-0003-2743-9008
Chao TangCenter for Quantitative Biology, Peking University, Beijing, China.ORCID 0000-0003-1474-3705
Lei ZhangCenter for Quantitative Biology, Peking University, Beijing, China.ORCID 0000-0001-9972-2051

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Morphogenesis is a precise and robust dynamic process during metazoan embryogenesis, consisting of both cell proliferation and cell migration. Despite the fact that much is known about specific regulations at molecular level, how cell proliferation and migration together drive the morphogenesis at cellular and organismic levels is not well understood. Using Caenorhabditis elegans as the model animal, we present a phase field model to compute early embryonic morphogenesis within a confined eggshell. With physical information about cell division obtained from three-dimensional time-lapse cellular imaging experiments, the model can precisely reproduce the early morphogenesis process as seen in vivo, including time evolution of location and morphology of each cell. Furthermore, the model can be used to reveal key cell-cell attractions critical to the development of C. elegans embryo. Our work demonstrates how genetic programming and physical forces collaborate to drive morphogenesis and provides a predictive model to decipher the underlying mechanism.

Indexed as

Models, BiologicalAnimalsCaenorhabditis elegansComputational BiologyEmbryonic DevelopmentEmbryo, Nonmammalian

Identifiers

PMID35030161
PMCPMC8794267

What Socratic holds

Textmetadata
LicenceCC BY
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 Socratic graph.