Evidence map›Paper›PMID 39420008›Full record

ArticleNPJ systems biology and applications2024

Stochastic Boolean model of normal and aberrant cell cycles in budding yeast.

Kittisak Taoma, John J Tyson, Teeraphan Laomettachit, Pavel Kraikivski

Abstract read
In one paragraph

Article in NPJ systems biology and applications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. 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

4 authors.

Kittisak TaomaBioinformatics and Systems Biology Program, School of Bioresources and Technology, King Mongkut's University of Technology Thonburi, Bangkok, 10150, Thailand.
John J TysonDepartment of Biological Sciences, Virginia Polytechnic Institute and State University, Blacksburg, VA, 24061, USA.ORCID 0000-0001-7560-6013
Teeraphan LaomettachitBioinformatics and Systems Biology Program, School of Bioresources and Technology, King Mongkut's University of Technology Thonburi, Bangkok, 10150, Thailand. teeraphan.lao@kmutt.ac.th.ORCID 0000-0003-3194-1391
Pavel KraikivskiDivision of Systems Biology, Academy of Integrated Science, Virginia Polytechnic Institute and State University, Blacksburg, VA, 24061, USA. pavelkr@vt.edu.ORCID 0000-0001-7742-0140

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The cell cycle of budding yeast is governed by an intricate protein regulatory network whose dysregulation can lead to lethal mistakes or aberrant cell division cycles. In this work, we model this network in a Boolean framework for stochastic simulations. Our model is sufficiently detailed to account for the phenotypes of 40 mutant yeast strains (83% of the experimentally characterized strains that we simulated) and also to simulate an endoreplicating strain (multiple rounds of DNA synthesis without mitosis) and a strain that exhibits 'Cdc14 endocycles' (periodic transitions between metaphase and anaphase). Because our model successfully replicates the observed properties of both wild-type yeast cells and many mutant strains, it provides a reasonable, validated starting point for more comprehensive stochastic-Boolean models of cell cycle controls. Such models may provide a better understanding of cell cycle anomalies in budding yeast and ultimately in mammalian cells.

Indexed as

Cell CycleModels, BiologicalSaccharomycetalesStochastic ProcessesCell Cycle ProteinsComputer SimulationDNA ReplicationMutationSaccharomyces cerevisiaeSaccharomyces cerevisiae ProteinsCell Cycle ProteinsSaccharomyces cerevisiae Proteins

Identifiers

PMID39420008
PMCPMC11487276

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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.