Evidence map›Paper›PMID 37074581›Full record

ReviewMethods in molecular biology (Clifton, N.J.)2023

Modeling Cellular Signaling Variability Based on Single-Cell Data: The TGFβ-SMAD Signaling Pathway.

Uddipan Sarma, Lorenz Ripka, Uchenna Alex Anyaegbunam, Stefan Legewie

Abstract readReview
PubMed Publisher
In one paragraph

Review in Methods in molecular biology (Clifton, N.J.), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

4 authors.

Uddipan Sarma *Institute of Molecular Biology (IMB), Mainz, Germany.
Lorenz Ripka *Institute of Molecular Biology (IMB), Mainz, Germany.
Uchenna Alex Anyaegbunam *Institute of Molecular Biology (IMB), Mainz, Germany.
Stefan LegewieInstitute of Molecular Biology (IMB), Mainz, Germany. legewie@ibmg.uni-stuttgart.de.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Nongenetic heterogeneity is key to cellular decisions, as even genetically identical cells respond in very different ways to the same external stimulus, e.g., during cell differentiation or therapeutic treatment of disease. Strong heterogeneity is typically already observed at the level of signaling pathways that are the first sensors of external inputs and transmit information to the nucleus where decisions are made. Since heterogeneity arises from random fluctuations of cellular components, mathematical models are required to fully describe the phenomenon and to understand the dynamics of heterogeneous cell populations. Here, we review the experimental and theoretical literature on cellular signaling heterogeneity, with special focus on the TGFβ/SMAD signaling pathway.

Indexed as

Models, TheoreticalSignal TransductionSmad ProteinsTransforming Growth Factor betaSmad ProteinsTransforming Growth Factor betaCell-to-cell variabilityHeterogeneityMathematical modelingNumerical simulationOrdinary differential equationsSignal transductionSingle cellsSMAD transcription factorsStochastic modelingTGFβ signaling

Identifiers

What OpenQuestion holds

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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.