Evidence map›Paper›PMID 39342398›Full record

ReviewMicrobiome2024

Networks as tools for defining emergent properties of microbiomes and their stability.

Kacie T Kajihara, Nicole A Hynson

Abstract readReview
In one paragraph

Review in Microbiome, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 90 papers.

0numbers the graph read from it
0cells of the map it votes in
90citing 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

90 citing papers in PubMed.

  1. Effect ofNutrients · 2026
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30 more citing papers are in PubMed but not listed here.

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

2 authors.

Kacie T KajiharaPacific Biosciences Research Center, University of Hawai'i at Mānoa, Honolulu, HI, 96822, USA. kaciekaj@hawaii.edu.
Nicole A HynsonPacific Biosciences Research Center, University of Hawai'i at Mānoa, Honolulu, HI, 96822, USA.

Funding

National Science Foundation 2124922
6 · The paper itself

Abstract

The potential promise of the microbiome to ameliorate a wide range of societal and ecological challenges, from disease prevention and treatment to the restoration of entire ecosystems, hinges not only on microbiome engineering but also on the stability of beneficial microbiomes. Yet the properties of microbiome stability remain elusive and challenging to discern due to the complexity of interactions and often intractable diversity within these communities of bacteria, archaea, fungi, and other microeukaryotes. Networks are powerful tools for the study of complex microbiomes, with the potential to elucidate structural patterns of stable communities and generate testable hypotheses for experimental validation. However, the implementation of these analyses introduces a cascade of dichotomies and decision trees due to the lack of consensus on best practices. Here, we provide a road map for network-based microbiome studies with an emphasis on discerning properties of stability. We identify important considerations for data preparation, network construction, and interpretation of network properties. We also highlight remaining limitations and outstanding needs for this field. This review also serves to clarify the varying schools of thought on the application of network theory for microbiome studies and to identify practices that enhance the reproducibility and validity of future work. Video Abstract.

Indexed as

ArchaeaBacteriaMicrobiotaEcosystemFungiHumansReproducibility of ResultsBacteriaCo-occurrence networksData scienceFungiMicrobiomeMulti-omicsStability

Identifiers

PMID39342398
PMCPMC11439251

What OpenQuestion 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 OpenQuestion graph.