Evidence map›Paper›PMID 31310618›Full record

ArticlePLoS computational biology2019

Analyzing pharmacological intervention points: A method to calculate external stimuli to switch between steady states in regulatory networks.

Tim Breitenbach, Chunguang Liang, Niklas Beyersdorf, Thomas Dandekar

Open access · goldAbstract read
In one paragraph

Article in PLoS computational biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
0.9field-weighted citation impact, top 27% 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

8 citing papers in PubMed, 15 citations in OpenAlex.

  1. Article
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  5. Alveolar Regeneration in COVID-19 Patients: A Network Perspective.International journal of molecular sciences · 2021
    Review
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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

4 authors at 1 institution in 1 country.

Tim BreitenbachLehrstuhl für Bioinformatik, Biozentrum, Universität Würzburg, Würzburg, Germany.
Chunguang LiangLehrstuhl für Bioinformatik, Biozentrum, Universität Würzburg, Würzburg, Germany.
Niklas BeyersdorfInstitut für Virologie und Immunbiologie, Universität Würzburg, Würzburg, Germany.
Thomas DandekarLehrstuhl für Bioinformatik, Biozentrum, Universität Würzburg, Würzburg, Germany.ORCID 0000-0003-1886-7625
University of Würzburg · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Once biological systems are modeled by regulatory networks, the next step is to include external stimuli, which model the experimental possibilities to affect the activity level of certain network's nodes, in a mathematical framework. Then, this framework can be interpreted as a mathematical optimal control framework such that optimization algorithms can be used to determine external stimuli which cause a desired switch from an initial state of the network to another final state. These external stimuli are the intervention points for the corresponding biological experiment to obtain the desired outcome of the considered experiment. In this work, the model of regulatory networks is extended to controlled regulatory networks. For this purpose, external stimuli are considered which can affect the activity of the network's nodes by activation or inhibition. A method is presented how to calculate a selection of external stimuli which causes a switch between two different steady states of a regulatory network. A software solution based on Jimena and Mathworks Matlab is provided. Furthermore, numerical examples are presented to demonstrate application and scope of the software on networks of 4 nodes, 11 nodes and 36 nodes. Moreover, we analyze the aggregation of platelets and the behavior of a basic T-helper cell protein-protein interaction network and its maturation towards Th0, Th1, Th2, Th17 and Treg cells in accordance with experimental data.

Indexed as

Computer SimulationModels, BiologicalProtein Interaction MapsT-Lymphocytes, Helper-Inducer

Identifiers

PMID31310618
PMCPMC6660093
OpenAlexW2958415029

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.