Evidence map›Paper›PMID 34238210›Full record

ArticleBMC bioinformatics2021

Predicting synchronized gene coexpression patterns from fibration symmetries in gene regulatory networks in bacteria.

Ian Leifer, Mishael Sánchez-Pérez, Cecilia Ishida, Hernán A Makse

Open access · goldAbstract read
In one paragraph

Article in BMC bioinformatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
0.7field-weighted citation impact, top 32% 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

10 citing papers in PubMed, 14 citations in OpenAlex.

  1. The role of fibration symmetries in geometric deep learning.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  2. Symmetries and synchronization from whole-neural activity in theProceedings of the National Academy of Sciences of the United States of America · 2025
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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

4 authors at 2 institutions in 2 countries.

Ian LeiferLevich Institute,Physics Department, City College of New York, New York, NY, 10031, USA.
Mishael Sánchez-PérezLevich Institute,Physics Department, City College of New York, New York, NY, 10031, USA.
Cecilia IshidaFaculty of Medicine and Biomedical Sciences, Autonomous University of Chihuahua, 31125, Chihuahua, Chihuahua, Mexico.
Hernán A MakseLevich Institute,Physics Department, City College of New York, New York, NY, 10031, USA. hmakse@ccny.cuny.edu.
City College of New York · USAutonomous University of Chihuahua · MX

Funding

Supplement: Network Methods for Brain Imaging with TumorsR01EB022720 · NIBIB · CITY COLLEGE OF NEW YORK · PI HOLODNY, ANDREI I, MAKSE, HERNAN · 2016 to 2018
$1.3M
Application of the principle of symmetry to neural circuitry: From building blocks to neural synchronization in the connectomeR01EB028157 · NIBIB · CITY COLLEGE OF NEW YORK · PI MAKSE, HERNAN, ZIMMER, MANUEL · 2020 to 2020
$1.1M
NIBIB NIH HHS R01 EB022720NIBIB NIH HHS R01 EB028157
6 · The paper itself

Abstract

backgroundGene regulatory networks coordinate the expression of genes across physiological states and ensure a synchronized expression of genes in cellular subsystems, critical for the coherent functioning of cells. Here we address the question whether it is possible to predict gene synchronization from network structure alone. We have recently shown that synchronized gene expression can be predicted from symmetries in the gene regulatory networks described by the concept of symmetry fibrations. We showed that symmetry fibrations partition the genes into groups called fibers based on the symmetries of their 'input trees', the set of paths in the network through which signals can reach a gene. In idealized dynamic gene expression models, all genes in a fiber are perfectly synchronized, while less idealized models-with gene input functions differencing between genes-predict symmetry breaking and desynchronization.

resultsTo study the functional role of gene fibers and to test whether some of the fiber-induced coexpression remains in reality, we analyze gene fibrations for the gene regulatory networks of E. coli and B. subtilis and confront them with expression data. We find approximate gene coexpression patterns consistent with symmetry fibrations with idealized gene expression dynamics. This shows that network structure alone provides useful information about gene synchronization, and suggest that gene input functions within fibers may be further streamlined by evolutionary pressures to realize a coexpression of genes.

conclusionsThus, gene fibrations provide a sound conceptual tool to describe tunable coexpression induced by network topology and shaped by mechanistic details of gene expression.

Indexed as

Escherichia coliGene Regulatory NetworksGene ExpressionPhenotype

Identifiers

PMID34238210
PMCPMC8265036
OpenAlexW3111998489

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.