Evidence map›Paper›PMID 40240448›Full record

ArticleScientific reports2025

Extreme events in gene regulatory networks with time-delays.

S Vinoth, S Leo Kingston, Sabarathinam Srinivasan, Suresh Kumarasamy, Tomasz Kapitaniak

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

S VinothCenter for Nonlinear and Complex Networks, SRM Institute of Science and Technology, Ramapuram, Chennai, 600 089, India.
S Leo KingstonDivision of Dynamics, Lodz University of Technology, Stefanowskiego 1/15, 90-924, Lodz, Poland. kingston.cnld@gmail.com.
Sabarathinam SrinivasanDepartment of Molecular Analytics, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences (SIMATS), Chennai, Tamilnadu, India.
Suresh KumarasamyCentre for Artificial Intelligence, Easwari Engineering College, Chennai, 600 089, India. sureshscience@gmail.com.
Tomasz KapitaniakDivision of Dynamics, Lodz University of Technology, Stefanowskiego 1/15, 90-924, Lodz, Poland.

Funding

Easwari Engineering College, Tamil Nadu SRM/EEC/RI/006.Narodowym Centrum Nauki 2018/29/B/ST8/00457, and 2021/43/B/ST8/00641SRM Institute of Science and Technology SRM/IST-RMP/RI/004
6 · The paper itself

Abstract

This work explores distinct complex dynamics of simplified two nodes of coupled gene regulatory networks with multiple delays in two self-inhibitory and mutually activated genes. We have identified the emergence of extreme events within a specific range of system parameter values. A detailed analysis of the time delay-induced emergence of extreme events is illustrated using bifurcation analysis, two-parameter phase diagrams, return maps, temporal plots, and probability density functions. The reasons behind the advent of extreme events are discussed in detail, with possible analogies to simplified two nodes of gene regulatory networks. The occasional large-amplitude bursting originated in the system via interior crisis-induced intermittency, Pomeau-Manneville intermittency, and the breakdown of quasiperiodic intermittency routes. Additionally, we have used various recurrence quantification statistical measures, such as mean recurrence time, determinism, and recurrence time entropy, to describe the transition from periodic or chaotic to unforeseen large deviations. Our approach shows that the sudden surge of variance and mean recurrence time at the transition points can be used as a new metric to detect the critical transitions of distinct extreme bursting events. The comprehensive overview of the interaction between gene regulatory networks, with insights into the formation of unusual dynamics, is beneficial to grasping different neuronal diseases.

Indexed as

Gene Regulatory NetworksModels, GeneticGene Expression RegulationTime FactorsExtreme eventsGene regulatory networksRecurrence quantification measuresTime-delay

Identifiers

PMID40240448
PMCPMC12003715

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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.