Evidence map›Paper›PMID 32123964›Full record

ArticleJournal of mathematical biology2020

Joining and decomposing reaction networks.

Elizabeth Gross, Heather Harrington, Nicolette Meshkat, Anne Shiu

Abstract read
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In one paragraph

Article in Journal of mathematical biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Oscillations and bistability in a model of ERK regulation.Journal of mathematical biology · 2019
    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.

Elizabeth GrossUniversity of Hawai'i at Mānoa, Honolulu, USA. egross@hawaii.edu.
Heather HarringtonUniversity of Oxford, Oxford, UK.
Nicolette MeshkatSanta Clara University, Santa Clara, USA.
Anne ShiuTexas A&M University, College Station, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In systems and synthetic biology, much research has focused on the behavior and design of single pathways, while, more recently, experimental efforts have focused on how cross-talk (coupling two or more pathways) or inhibiting molecular function (isolating one part of the pathway) affects systems-level behavior. However, the theory for tackling these larger systems in general has lagged behind. Here, we analyze how joining networks (e.g., cross-talk) or decomposing networks (e.g., inhibition or knock-outs) affects three properties that reaction networks may possess-identifiability (recoverability of parameter values from data), steady-state invariants (relationships among species concentrations at steady state, used in model selection), and multistationarity (capacity for multiple steady states, which correspond to multiple cell decisions). Specifically, we prove results that clarify, for a network obtained by joining two smaller networks, how properties of the smaller networks can be inferred from or can imply similar properties of the original network. Our proofs use techniques from computational algebraic geometry, including elimination theory and differential algebra.

Indexed as

Models, BiologicalSignal TransductionSystems BiologyAnimalsApoptosisBiochemical PhenomenaHumansKineticsLinear ModelsMathematical ConceptsMetabolic Networks and PathwaysSynthetic BiologyGröbner basisIdentifiabilityMass-action kineticsMultistationarityReaction networkSteady-state invariant

Identifiers

PMID32123964

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.