Evidence map›Paper›PMID 29525203›Full record

ArticleCell systems2018

Modeling Cell-to-Cell Communication Networks Using Response-Time Distributions.

Kevin Thurley, Lani F Wu, Steven J Altschuler

Abstract read
In one paragraph

Article in Cell systems, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.

0numbers the graph read from it
0cells of the map it votes in
34citing 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

34 citing papers in PubMed.

  1. Review
  2. Article
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  7. Review
  8. Article
  9. Timed Pulses in DNA Strand Displacement Reactions.Journal of the American Chemical Society · 2023
    Article
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  11. Review
  12. Article
  13. Article
  14. Article
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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

3 authors.

Kevin ThurleyDepartment of Pharmaceutical Chemistry, University of California San Francisco, San Francisco, CA 94158, USA. Electronic address: kevin.thurley@drfz.de.
Lani F WuDepartment of Pharmaceutical Chemistry, University of California San Francisco, San Francisco, CA 94158, USA. Electronic address: lani.wu@ucsf.edu.
Steven J AltschulerDepartment of Pharmaceutical Chemistry, University of California San Francisco, San Francisco, CA 94158, USA. Electronic address: steven.altschuler@ucsf.edu.

Funding

Maximizing the predictive power of high-throughput, microscopy-based phenotypic screensR01CA184984 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI WU, LANI F · 2014 to 2025
$4.7M
(PQD1) An Iterative Approach for Overcoming Evolving Targeted Therapy ResistanceR01CA185404 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI WU, LANI F · 2014 to 2017
$1.3M
Systems-level role of GSK3 in colonic epithelium homeostasis and drug resistanceR01GM112690 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI ALTSCHULER, STEVEN J · 2015 to 2018
$1.3M
NCI NIH HHS R01 CA184984NCI NIH HHS R01 CA185404NIGMS NIH HHS R01 GM112690
6 · The paper itself

Abstract

Cell-to-cell communication networks have critical roles in coordinating diverse organismal processes, such as tissue development or immune cell response. However, compared with intracellular signal transduction networks, the function and engineering principles of cell-to-cell communication networks are far less understood. Major complications include: cells are themselves regulated by complex intracellular signaling networks; individual cells are heterogeneous; and output of any one cell can recursively become an additional input signal to other cells. Here, we make use of a framework that treats intracellular signal transduction networks as "black boxes" with characterized input-to-output response relationships. We study simple cell-to-cell communication circuit motifs and find conditions that generate bimodal responses in time, as well as mechanisms for independently controlling synchronization and delay of cell-population responses. We apply our modeling approach to explain otherwise puzzling data on cytokine secretion onset times in T cells. Our approach can be used to predict communication network structure using experimentally accessible input-to-output measurements and without detailed knowledge of intermediate steps.

Indexed as

AlgorithmsCell CommunicationComputer SimulationCytokinesHumansModels, BiologicalSignal TransductionT-LymphocytesCytokinescell-to-cell communicationcytokine signalsfirst-passage timeresponse-time modeling

Identifiers

PMID29525203
PMCPMC5913757

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.