Evidence map›Paper›PMID 23270532›Full record

ArticleBMC systems biology2012

Metabolic flux-based modularity using shortest retroactive distances.

Gautham Vivek Sridharan, Michael Yi, Soha Hassoun, Kyongbum Lee

Abstract read
In one paragraph

Article in BMC systems biology, 2012. 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

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2 · The registry

The trial behind it

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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
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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.

Gautham Vivek SridharanDepartment of Chemical and Biological Engineering, Tufts University, 4 Colby Street, Room 150, Medford, MA 02155, USA.
Michael Yi
Soha Hassoun
Kyongbum Lee

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGraph-based modularity analysis has emerged as an important tool to study the functional organization of biological networks. However, few methods are available to study state-dependent changes in network modularity using biological activity data. We develop a weighting scheme, based on metabolic flux data, to adjust the interaction distances in a reaction-centric graph model of a metabolic network. The weighting scheme was combined with a hierarchical module assignment algorithm featuring the preservation of metabolic cycles to examine the effects of cellular differentiation and enzyme inhibitions on the functional organization of adipocyte metabolism.

resultsOur analysis found that the differences between various metabolic states primarily involved the assignment of two specific reactions in fatty acid synthesis and glycerogenesis. Our analysis also identified cyclical interactions between reactions that are robust with respect to metabolic state, suggesting possible co-regulation. Comparisons based on cyclical interaction distances between reaction pairs suggest that the modular organization of adipocyte metabolism is stable with respect to the inhibition of an enzyme, whereas a major physiological change such as cellular differentiation leads to a more substantial reorganization.

conclusionTaken together, our results support the notion that network modularity is influenced by both the connectivity of the network's components as well as the relative engagements of the connections.

Indexed as

Metabolic Networks and PathwaysAdipocytesCell DifferentiationComputational BiologyComputer GraphicsEnzyme InhibitorsModels, BiologicalEnzyme Inhibitors

Identifiers

PMID23270532
PMCPMC3556310

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.