Evidence map›Paper›PMID 24816736›Full record

ArticlePloS one2014

A stochastic model correctly predicts changes in budding yeast cell cycle dynamics upon periodic expression of CLN2.

Cihan Oguz, Alida Palmisano, Teeraphan Laomettachit, Layne T Watson, William T Baumann, John J Tyson

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.4field-weighted citation impact, top 20% 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

3 citing papers in PubMed, 10 citations in OpenAlex.

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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

6 authors at 2 institutions in 2 countries.

Cihan OguzDepartment of Biological Sciences, Virginia Tech, Blacksburg, Virginia, United States of America.
Alida PalmisanoDepartment of Biological Sciences, Virginia Tech, Blacksburg, Virginia, United States of America; Department of Computer Science, Virginia Tech, Blacksburg, Virginia, United States of America.
Teeraphan LaomettachitBioinformatics and Systems Biology Program, School of Bioresources and Technology, King Mongkut's University of Technology Thonburi, Bangkok, Thailand.
Layne T WatsonDepartment of Computer Science, Virginia Tech, Blacksburg, Virginia, United States of America; Department of Mathematics, Virginia Tech, Blacksburg, Virginia, United States of America; Department of Aerospace and Ocean Engineering, Virginia Tech, Blacksburg, Virginia, United States of America.
William T BaumannDepartment of Electrical and Computer Engineering, Virginia Tech, Blacksburg, Virginia, United States of America.
John J TysonDepartment of Biological Sciences, Virginia Tech, Blacksburg, Virginia, United States of America.
Virginia Tech · USKing Mongkut's University of Technology Thonburi · TH

Funding

Stochastic Models of Cell Cycle Regulation in EukaryotesR01GM078989 · NIGMS · VIRGINIA POLYTECHNIC INST AND ST UNIV · PI PECCOUD, JEAN M, TYSON, JOHN J. · 2006 to 2018
$5.3M
NIGMS NIH HHS R01 GM078989
6 · The paper itself

Abstract

In this study, we focus on a recent stochastic budding yeast cell cycle model. First, we estimate the model parameters using extensive data sets: phenotypes of 110 genetic strains, single cell statistics of wild type and cln3 strains. Optimization of stochastic model parameters is achieved by an automated algorithm we recently used for a deterministic cell cycle model. Next, in order to test the predictive ability of the stochastic model, we focus on a recent experimental study in which forced periodic expression of CLN2 cyclin (driven by MET3 promoter in cln3 background) has been used to synchronize budding yeast cell colonies. We demonstrate that the model correctly predicts the experimentally observed synchronization levels and cell cycle statistics of mother and daughter cells under various experimental conditions (numerical data that is not enforced in parameter optimization), in addition to correctly predicting the qualitative changes in size control due to forced CLN2 expression. Our model also generates a novel prediction: under frequent CLN2 expression pulses, G1 phase duration is bimodal among small-born cells. These cells originate from daughters with extended budded periods due to size control during the budded period. This novel prediction and the experimental trends captured by the model illustrate the interplay between cell cycle dynamics, synchronization of cell colonies, and size control in budding yeast.

Indexed as

Cell CycleGene Expression Regulation, FungalModels, BiologicalCell SizeCyclinsMutationSaccharomyces cerevisiaeSaccharomyces cerevisiae ProteinsStochastic ProcessesCLN2 protein, S cerevisiaeCyclinsSaccharomyces cerevisiae Proteins

Identifiers

PMID24816736
PMCPMC4016136
OpenAlexW1965016303

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.