Evidence map›Paper›PMID 40047537›Full record

ArticleeLife2025

Evaluation of information flows in the RAS-MAPK system using transfer entropy measurements.

Nobuhisa Umeki, Yoshiyuki Kabashima, Yasushi Sako

Abstract read
In one paragraph

Article in eLife, 2025. 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

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

1 citing paper in PubMed.

  1. Quantifying Information Exchange Between Cells in Inflammaging.Bioengineering (Basel, Switzerland) · 2026
    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

3 authors.

Nobuhisa UmekiCellular Informatics Laboratory, RIKEN, Cluster for Pioneering Research, Wako, Japan.
Yoshiyuki KabashimaInstitute for Physics of Intelligence, The University of Tokyo, Bunkyo-ku, Japan.
Yasushi SakoCellular Informatics Laboratory, RIKEN, Cluster for Pioneering Research, Wako, Japan.ORCID https://orcid.org/0000-0002-5707-5455

Funding

Collaborative Research in Engineering, Science and Technology Centre JPMJCR1912Ministry of Education, Culture, Sports, Science and Technology 19H05647Ministry of Education, Culture, Sports, Science and Technology 22H05117
6 · The paper itself

Abstract

The RAS-MAPK system plays an important role in regulating various cellular processes, including growth, differentiation, apoptosis, and transformation. Dysregulation of this system has been implicated in genetic diseases and cancers affecting diverse tissues. To better understand the regulation of this system, we employed information flow analysis based on transfer entropy (TE) between the activation dynamics of two key elements in cells stimulated with EGF: SOS, a guanine nucleotide exchanger for the small GTPase RAS, and RAF, a RAS effector serine/threonine kinase. TE analysis allows for model-free assessment of the timing, direction, and strength of the information flow regulating the system response. We detected significant amounts of TE in both directions between SOS and RAF, indicating feedback regulation. Importantly, the amount of TE did not simply follow the input dose or the intensity of the causal reaction, demonstrating the uniqueness of TE. TE analysis proposed regulatory networks containing multiple tracks and feedback loops and revealed temporal switching in the reaction pathway primarily responsible for reaction control. This proposal was confirmed by the effects of an MEK inhibitor on TE. Furthermore, TE analysis identified the functional disorder of a SOS mutation associated with Noonan syndrome

Indexed as

MAP Kinase Signaling Systemras ProteinsEntropyEpidermal Growth FactorHumansEpidermal Growth Factorras Proteinscomputational biologyhumanRAS/MAPK systemsignal processingsingle-cell analysissystems biologytransfer entropy

Identifiers

PMID40047537
PMCPMC11884788

What OpenQuestion holds

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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.