Evidence map›Paper›PMID 42782447›Full record

ArticleAdvances in experimental medicine and biology2026

The Emergent Architecture of Autonomous Clocks Described by Computational Algorithms of Regulatory Networks.

Breschine Cummins, Marcio Gameiro, Konstantin Mischaikow, Tomas Gedeon

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Article in Advances in experimental medicine and biology, 2026. 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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0cells of the map it votes in
0citing papers in PubMed
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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

4 authors.

Breschine CumminsDepartment of Mathematical Sciences, Montana State University, Bozeman, MT, USA. breschine.cummins@montana.edu.
Marcio GameiroDepartment of Mathematics, Rutgers University, New Brunswick, NJ, USA.
Konstantin MischaikowDepartment of Mathematics, Rutgers University, New Brunswick, NJ, USA.
Tomas GedeonDepartment of Mathematical Sciences, Montana State University, Bozeman, MT, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Autonomous oscillators in systems biology are often mathematically expressed as regulatory network models. These models are interrogated to predict oscillator behavior under various environmental conditions. The potential suite of dynamical behaviors arising from a regulatory network model is rich and varied, as one might expect of a complex system. Therefore, a mathematical model has the capability to predict previously unobserved biological oscillator behavior that arises under untested conditions. We present a computational method that describes the full suite of dynamical behaviors of a network model, enabling both mechanistic understanding of experimental observations and prediction of unexpected dynamics. These ideas are presented through example network models, including some relevant to the yeast cell cycle.

Indexed as

AlgorithmsBiological ClocksGene Regulatory NetworksModels, BiologicalSystems BiologyCell CycleComputer SimulationSaccharomyces cerevisiaeComputational biologyDSGRNDynamical attractorGenetic regulatory networksHysteresisMathematical biologyMorse graphMultilevel discrete modelNetwork dynamicsParameter graphRepressilatorState transition graph

Identifiers

PMID42782447

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.