Evidence map›Paper›PMID 40894086›Full record

ArticleStudies in applied mathematics (Cambridge, Mass.)2025

Detecting (the Absence of) Species Interactions in Microbial Ecological Systems.

Thomas Beardsley, Megan Behringer, Natalia L Komarova

Abstract read
In one paragraph

Article in Studies in applied mathematics (Cambridge, Mass.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Thomas BeardsleyDepartment of Mathematics, University of California Irvine, Irvine, California, USA.
Megan BehringerDepartment of Biological Sciences, Vanderbilt University, Nashville, Tennessee, USA.ORCID 0000-0001-7036-6014
Natalia L KomarovaDepartment of Mathematics, University of California Irvine, Irvine, California, USA.ORCID 0000-0003-4876-0343

Funding

Using Experimental Evolution to Evaluate Environmental Effects on Microbial Mutation and AdaptationR35GM150625 · NIGMS · VANDERBILT UNIVERSITY · PI Megan Grace Behringer · 2023 to 2026
$1.8M
NIGMS NIH HHS R35 GM150625
6 · The paper itself

Abstract

Microbial communities are complex ecological systems of organisms that evolve in time, with new variants created, while others disappear. Understanding how species interact within communities can help us shed light into the mechanisms that drive ecosystem processes. We studied systems with serial propagation, where the community is kept alive by taking a subsample at regular intervals and replating it in fresh medium. The data that are usually collected consist of the % of the population for each of the species, at several time points. In order to utilize this type of data, we formulated a system of equations (based on the generalized Lotka-Volterra model) and derived conditions of species noninteraction. This was possible to achieve by reformulating the problem as a problem of finding feasibility domains, which can be solved by a number of efficient algorithms. This methodology provides a cost-effective way to investigate interactions in microbial communities.

Indexed as

dynamics systemsfeasibility domainsLotka–Volterra equations

Identifiers

PMID40894086
PMCPMC12392786

What OpenQuestion holds

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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.