Evidence map›Paper›PMID 24041013›Full record

ReviewBMC systems biology2013

Topology of molecular interaction networks.

Wynand Winterbach, Piet Van Mieghem, Marcel Reinders, Huijuan Wang, Dick de Ridder

Abstract readReview
In one paragraph

Review in BMC systems biology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 51 papers.

0numbers the graph read from it
0cells of the map it votes in
51citing 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

51 citing papers in PubMed.

  1. The challenge of distinguishing living from non-living entities.Theory in biosciences = Theorie in den Biowissenschaften · 2026
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  5. Bioremediation Potential ofMicroorganisms · 2024
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  8. Microbiome modeling: a beginner's guide.Frontiers in microbiology · 2024
    Review
  9. Article
  10. Review
  11. Article
  12. Article
  13. Quantitative systems pharmacology of the eye: Tools and data for ocular QSP.CPT: pharmacometrics & systems pharmacology · 2023
    Review
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. 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

5 authors.

Wynand WinterbachNetwork Architectures and Services, Department of Intelligent Systems, Faculty of Electrical Engineering, Mathematics and Computer Science, Delft University of Technology, P,O, Box 5031, 2600 GA Delft, The Netherlands. w.winterbach@tudelft.nl.
Piet Van Mieghem
Marcel Reinders
Huijuan Wang
Dick de Ridder

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Molecular interactions are often represented as network models which have become the common language of many areas of biology. Graphs serve as convenient mathematical representations of network models and have themselves become objects of study. Their topology has been intensively researched over the last decade after evidence was found that they share underlying design principles with many other types of networks.Initial studies suggested that molecular interaction network topology is related to biological function and evolution. However, further whole-network analyses did not lead to a unified view on what this relation may look like, with conclusions highly dependent on the type of molecular interactions considered and the metrics used to study them. It is unclear whether global network topology drives function, as suggested by some researchers, or whether it is simply a byproduct of evolution or even an artefact of representing complex molecular interaction networks as graphs.Nevertheless, network biology has progressed significantly over the last years. We review the literature, focusing on two major developments. First, realizing that molecular interaction networks can be naturally decomposed into subsystems (such as modules and pathways), topology is increasingly studied locally rather than globally. Second, there is a move from a descriptive approach to a predictive one: rather than correlating biological network topology to generic properties such as robustness, it is used to predict specific functions or phenotypes.Taken together, this change in focus from globally descriptive to locally predictive points to new avenues of research. In particular, multi-scale approaches are developments promising to drive the study of molecular interaction networks further.

Indexed as

MetabolismHumansStatistics as TopicSystems Biology

Identifiers

PMID24041013
PMCPMC4231395

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.