Evidence map›Paper›PMID 38188223›Full record

ArticlePlant phenomics (Washington, D.C.)2024

Genome-Wide Network Analysis of Above- and Below-Ground Co-growth in

Kaiyan Lu, Huiying Gong, Dengcheng Yang, Meixia Ye, Qing Fang, Xiao-Yu Zhang, Rongling Wu

Abstract read
In one paragraph

Article in Plant phenomics (Washington, D.C.), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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.

Kaiyan LuCollege of Science, Beijing Forestry University, Beijing 100083, P. R. China.
Huiying GongCenter for Computational Biology, College of Biological Sciences and Technology, Beijing Forestry University, Beijing 100083, P. R. China.
Dengcheng YangCenter for Computational Biology, College of Biological Sciences and Technology, Beijing Forestry University, Beijing 100083, P. R. China.
Meixia YeCenter for Computational Biology, College of Biological Sciences and Technology, Beijing Forestry University, Beijing 100083, P. R. China.
Qing FangFaculty of Science, Yamagata University, Yamagata 990, Japan.
Xiao-Yu ZhangCollege of Science, Beijing Forestry University, Beijing 100083, P. R. China.ORCID https://orcid.org/0000-0002-2794-3848
Rongling WuYanqi Lake Beijing Institute of Mathematical Sciences and Applications, Beijing 101408, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Tree growth is the consequence of developmental interactions between above- and below-ground compartments. However, a comprehensive view of the genetic architecture of growth as a cohesive whole is poorly understood. We propose a systems biology approach for mapping growth trajectories in genome-wide association studies viewing growth as a complex (phenotypic) system in which above- and below-ground components (or traits) interact with each other to mediate systems behavior. We further assume that trait-trait interactions are controlled by a genetic system composed of many different interactive genes and integrate the Lotka-Volterra predator-prey model to dissect phenotypic and genetic systems into pleiotropic and epistatic interaction components by which the detailed genetic mechanism of above- and below-ground co-growth can be charted. We apply the approach to analyze linkage mapping data of

Identifiers

PMID38188223
PMCPMC10769449

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Registered trials

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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.