Evidence map›Paper›PMID 28725464›Full record

ArticleNPJ systems biology and applications2015

From START to FINISH: computational analysis of cell cycle control in budding yeast.

Pavel Kraikivski, Katherine C Chen, Teeraphan Laomettachit, T M Murali, John J Tyson

Open access · goldAbstract read
In one paragraph

Article in NPJ systems biology and applications, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers.

0numbers the graph read from it
0cells of the map it votes in
42citing papers in PubMed
3.5field-weighted citation impact, top 7% 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

42 citing papers in PubMed, 80 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Review
  8. Article
  9. Article
  10. Article
  11. Mathematical Models of Death Signaling Networks.Entropy (Basel, Switzerland) · 2022
    Review
  12. Article
  13. Article
  14. Review
  15. Article
  16. Article
  17. Article
  18. Towards a synthetic cell cycle.Nature communications · 2021
    Review
  19. Article
  20. Review
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

5 authors at 2 institutions in 2 countries.

Pavel KraikivskiDepartment of Biological Sciences, Virginia Polytechnic Institute and State University, Blacksburg, VA, USA.
Katherine C ChenDepartment of Biological Sciences, Virginia Polytechnic Institute and State University, Blacksburg, VA, USA.
Teeraphan LaomettachitBioinformatics and Systems Biology Program, King Mongkut's University of Technology, Thonburi, Bang Khun Thian, Bangkok, Thailand.
T M MuraliDepartment of Computer Science, Virginia Polytechnic Institute and State University, Blacksburg, VA, USA.
John J TysonDepartment of Biological Sciences, Virginia Polytechnic Institute and State University, Blacksburg, VA, USA.ORCID 0000-0001-7560-6013
Virginia Tech · USKing Mongkut's University of Technology Thonburi · TH

Funding

Integrating Top-Down and Bottom-Up Models in Systems Biology with Application toR01GM095955 · NIGMS · VIRGINIA POLYTECHNIC INST AND ST UNIV · PI MURALI, T M · 2011 to 2015
$2.0M
NIGMS NIH HHS R01 GM095955
6 · The paper itself

Abstract

In the cell division cycle of budding yeast, START refers to a set of tightly linked events that prepare a cell for budding and DNA replication, and FINISH denotes the interrelated events by which the cell exits from mitosis and divides into mother and daughter cells. On the basis of recent progress made by molecular biologists in characterizing the genes and proteins that control START and FINISH, we crafted a new mathematical model of cell cycle progression in yeast. Our model exploits a natural separation of time scales in the cell cycle control network to construct a system of differential-algebraic equations for protein synthesis and degradation, post-translational modifications, and rapid formation and dissociation of multimeric complexes. The model provides a unified account of the observed phenotypes of 257 mutant yeast strains (98% of the 263 strains in the data set used to constrain the model). We then use the model to predict the phenotypes of 30 novel combinations of mutant alleles. Our comprehensive model of the molecular events controlling cell cycle progression in budding yeast has both explanatory and predictive power. Future experimental tests of the model's predictions will be useful to refine the underlying molecular mechanism, to constrain the adjustable parameters of the model, and to provide new insights into how the cell division cycle is regulated in budding yeast.

Identifiers

PMID28725464
PMCPMC5516803
OpenAlexW2283051572

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-SA
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.