Evidence map›Paper›PMID 30240747›Full record

ArticleiScience2018

Controlling Cell Fate Specification System by Key Genes Determined from Network Structure.

Kenji Kobayashi, Kazuki Maeda, Miki Tokuoka, Atsushi Mochizuki, Yutaka Satou

Abstract read
In one paragraph

Article in iScience, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing 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

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

18 citing papers in PubMed.

  1. Network topology creates independent control of multiple checkpoints in the cell cycle system.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Review
  8. Mathematical modeling for developmental processes.Development, growth & differentiation · 2023
    Review
  9. Article
  10. Article
  11. Leveraging network structure in nonlinear control.NPJ systems biology and applications · 2022
    Review
  12. NETISCE: a network-based tool for cell fate reprogramming.NPJ systems biology and applications · 2022
    Article
  13. Article
  14. Article
  15. Review
  16. The AscidiaFrontiers in cell and developmental biology · 2021
    Article
  17. Review
  18. 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

5 authors.

Kenji KobayashiDepartment of Zoology, Graduate School of Science, Kyoto University, Sakyo, Kyoto 606-8502, Japan; CREST, Japan Science and Technology Agency, 4-1-8 Honcho, Kawaguchi, Saitama 332-0012, Japan.
Kazuki MaedaCREST, Japan Science and Technology Agency, 4-1-8 Honcho, Kawaguchi, Saitama 332-0012, Japan; Department of Mathematical Sciences, School of Science and Technology, Kwansei Gakuin University, 2-1 Gakuen, Sanda, Hyogo 669-1337, Japan.
Miki TokuokaDepartment of Zoology, Graduate School of Science, Kyoto University, Sakyo, Kyoto 606-8502, Japan; CREST, Japan Science and Technology Agency, 4-1-8 Honcho, Kawaguchi, Saitama 332-0012, Japan.
Atsushi MochizukiCREST, Japan Science and Technology Agency, 4-1-8 Honcho, Kawaguchi, Saitama 332-0012, Japan; Theoretical Biology Laboratory, RIKEN, Wako, Saitama 351-0198, Japan; Institute for Frontier Life and Medical Sciences, Kyoto University, Sakyo, Kyoto 606-8507, Japan. Electronic address: mochi@riken.jp.
Yutaka SatouDepartment of Zoology, Graduate School of Science, Kyoto University, Sakyo, Kyoto 606-8502, Japan; CREST, Japan Science and Technology Agency, 4-1-8 Honcho, Kawaguchi, Saitama 332-0012, Japan. Electronic address: yutaka@ascidian.zool.kyoto-u.ac.jp.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Network structures describing regulation between biomolecules have been determined in many biological systems. Dynamics of molecular activities based on such networks are considered to be the origin of many biological functions. Recently, it has been proved mathematically that key nodes for controlling dynamics in networks are identified from network structure alone. Here, we applied this theory to a gene regulatory network for the cell fate specification of seven tissues in the ascidian embryo and found that this network, which consisted of 92 factors, had five key molecules. By controlling the activities of these key molecules, the specific gene expression of six of seven tissues observed in the embryo was successfully reproduced. Since this method is applicable to all nonlinear dynamic systems, we propose this method as a tool for controlling gene regulatory networks and reprogramming cell fates.

Indexed as

BioinformaticsComplex System BiologyExperimental Models in Systems BiologyMathematical Biosciences

Identifiers

PMID30240747
PMCPMC6147236

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.