Evidence map›Paper›PMID 24642504›Full record

ArticlePloS one2014

Mapping network motif tunability and robustness in the design of synthetic signaling circuits.

Sergio Iadevaia, Luay K Nakhleh, Robert Azencott, Prahlad T Ram

Abstract read
In one paragraph

Article in PloS one, 2014. 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. Regulating cellular cyclic adenosine monophosphate: "Sources," "sinks," and now, "tunable valves".Wiley interdisciplinary reviews. Systems biology and medicine · 2020
    Review
  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.

Sergio IadevaiaDepartment of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, Texas, United States of America.
Luay K NakhlehDepartment of Computer Science, Rice University, Houston, Texas, United States of America.
Robert AzencottDepartment of Mathematics, University of Houston, Houston, Texas, United States of America.
Prahlad T RamDepartment of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, Texas, United States of America.

Funding

Systems-Based Predictions of Responses to Cancer TherapyU54CA112970 · NCI · UNIVERSITY OF CALIF-LAWRENC BERKELEY LAB · PI GRAY, JOE W. · 2004 to 2014
$27.1M
Determinants of signaling network regulation in combinatorial targeted therapiesR01CA125109 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI RAM, PRAHLAD T · 2008 to 2010
$1.1M
NCI NIH HHS R01 CA125109NCI NIH HHS R01CA125109NCI NIH HHS U54 CA112970
6 · The paper itself

Abstract

Cellular networks are highly dynamic in their function, yet evolutionarily conserved in their core network motifs or topologies. Understanding functional tunability and robustness of network motifs to small perturbations in function and structure is vital to our ability to synthesize controllable circuits. In establishing core sets of network motifs, we selected topologies that are overrepresented in mammalian networks, including the linear, feedback, feed-forward, and bifan circuits. Static and dynamic tunability of network motifs were defined as the motif ability to respectively attain steady-state or transient outputs in response to pre-defined input stimuli. Detailed computational analysis suggested that static tunability is insensitive to the circuit topology, since all of the motifs displayed similar ability to attain predefined steady-state outputs in response to constant inputs. Dynamic tunability, in contrast, was tightly dependent on circuit topology, with some motifs performing superiorly in achieving observed time-course outputs. Finally, we mapped dynamic tunability onto motif topologies to determine robustness of motif structures to changes in topology and identify design principles for the rational assembly of robust synthetic networks.

Indexed as

Gene Expression RegulationGene Regulatory NetworksModels, BiologicalAnimalsComputer SimulationFeedback, PhysiologicalLinear ModelsMammalsNucleotide MotifsSignal Transduction

Identifiers

PMID24642504
PMCPMC3958390

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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.