Evidence map›Paper›PMID 23593470›Full record

ArticlePloS one2013

Does habitat variability really promote metabolic network modularity?

Kazuhiro Takemoto

Erratum issuedOpen access · goldAbstract read
In one paragraph

Article in PloS one, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.5field-weighted citation impact, top 19% 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, 21 citations in OpenAlex.

  1. Article
  2. Article
  3. Evolutionary design principles in metabolism.Proceedings. Biological sciences · 2019
    Review
  4. Flux-dependent graphs for metabolic networks.NPJ systems biology and applications · 2018
    Article
  5. Article
  6. Article
  7. Review
  8. Article
4 · The record

Corrections and comments

  • Erratum issued
5 · Who and what money

Authors and funding

1 author at 1 institution in 1 country.

Kazuhiro TakemotoDepartment of Bioscience and Bioinformatics, Kyushu Institute of Technology, Kawazu, Iizuka Fukuoka, Japan. takemoto@bio.kyutech.ac.jp
Kyushu Institute of Technology · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The hypothesis that variability in natural habitats promotes modular organization is widely accepted for cellular networks. However, results of some data analyses and theoretical studies have begun to cast doubt on the impact of habitat variability on modularity in metabolic networks. Therefore, we re-evaluated this hypothesis using statistical data analysis and current metabolic information. We were unable to conclude that an increase in modularity was the result of habitat variability. Although horizontal gene transfer was also considered because it may contribute for survival in a variety of environments, closely related to habitat variability, and is known to be positively correlated with network modularity, such a positive correlation was not concluded in the latest version of metabolic networks. Furthermore, we demonstrated that the previously observed increase in network modularity due to habitat variability and horizontal gene transfer was probably due to a lack of available data on metabolic reactions. Instead, we determined that modularity in metabolic networks is dependent on species growth conditions. These results may not entirely discount the impact of habitat variability and horizontal gene transfer. Rather, they highlight the need for a more suitable definition of habitat variability and a more careful examination of relationships of the network modularity with horizontal gene transfer, habitats, and environments.

Indexed as

EcosystemMetabolic Networks and PathwaysDatabases as TopicGene Transfer, HorizontalSpecies Specificity

Identifiers

PMID23593470
PMCPMC3625173
OpenAlexW1983049875

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.