Evidence mapPaperPMID 38587642Full record

ReviewMicrobial ecology2024

Modeling Microbial Community Networks: Methods and Tools for Studying Microbial Interactions.

Shanchana Srinivasan, Apoorva Jnana, Thokur Sreepathy Murali

Open access · hybridAbstract readReview
In one paragraph

Review in Microbial ecology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed
12.2field-weighted citation impact, top 1% of its field
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

34 citing papers in PubMed, 52 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Review
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Silver Nanoparticle Priming Enhanced Seed Germination inNanomaterials (Basel, Switzerland) · 2026
    Article
  12. Article
  13. Review
  14. Article
  15. Evaluating Metabolic Support in Pairwise Microbial Communities Using MetQuest.Methods in molecular biology (Clifton, N.J.) · 2026
    Article
  16. Article
  17. Review
  18. Article
  19. Article
  20. 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

3 authors at 1 institution in 1 country.

Shanchana Srinivasan *Department of Public Health Genomics, Manipal School of Life Sciences, Manipal Academy of Higher Education, Manipal, 576104, India.
Apoorva Jnana *Department of Public Health Genomics, Manipal School of Life Sciences, Manipal Academy of Higher Education, Manipal, 576104, India.
Thokur Sreepathy MuraliDepartment of Public Health Genomics, Manipal School of Life Sciences, Manipal Academy of Higher Education, Manipal, 576104, India. murali.ts@manipal.edu.ORCID http://orcid.org/0000-0003-1563-8077
Manipal Academy of Higher Education · IN

Funding

Science and Engineering Research Board CRG/2022/003227
6 · The paper itself

Abstract

Microbial interactions function as a fundamental unit in complex ecosystems. By characterizing the type of interaction (positive, negative, neutral) occurring in these dynamic systems, one can begin to unravel the role played by the microbial species. Towards this, various methods have been developed to decipher the function of the microbial communities. The current review focuses on the various qualitative and quantitative methods that currently exist to study microbial interactions. Qualitative methods such as co-culturing experiments are visualized using microscopy-based techniques and are combined with data obtained from multi-omics technologies (metagenomics, metabolomics, metatranscriptomics). Quantitative methods include the construction of networks and network inference, computational models, and development of synthetic microbial consortia. These methods provide a valuable clue on various roles played by interacting partners, as well as possible solutions to overcome pathogenic microbes that can cause life-threatening infections in susceptible hosts. Studying the microbial interactions will further our understanding of complex less-studied ecosystems and enable design of effective frameworks for treatment of infectious diseases.

Indexed as

Microbial InteractionsMicrobiotaCoculture TechniquesCommunity NetworksHumansMicrobial ConsortiaDynamic modelingMicrobial interactionsMicrobiomeNetwork inference

Identifiers

PMID38587642
PMCPMC11001700
OpenAlexW4394575823

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.