Evidence map›Paper›PMID 20236959›Full record

ArticleJournal of the Royal Society, Interface2010

Topological network alignment uncovers biological function and phylogeny.

Oleksii Kuchaiev, Tijana Milenkovic, Vesna Memisevic, Wayne Hayes, Natasa Przulj

Abstract readComparative Study
In one paragraph

Article in Journal of the Royal Society, Interface, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 87 papers.

0numbers the graph read from it
0cells of the map it votes in
87citing 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

87 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Network-Based Structural Alignment of RNA Sequences Using TOPAS.Methods in molecular biology (Clifton, N.J.) · 2023
    Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Pairwise Biological Network Alignment Based on Discrete Bat Algorithm.Computational and mathematical methods in medicine · 2021
    Article
  17. Review
  18. Article
  19. Review
  20. Article

27 more citing papers are in PubMed but not listed here.

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.

Oleksii KuchaievDepartment of Computer Science, University of California, Irvine, CA 92697-3435, USA.
Tijana Milenkovic
Vesna Memisevic
Wayne Hayes
Natasa Przulj

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Sequence comparison and alignment has had an enormous impact on our understanding of evolution, biology and disease. Comparison and alignment of biological networks will probably have a similar impact. Existing network alignments use information external to the networks, such as sequence, because no good algorithm for purely topological alignment has yet been devised. In this paper, we present a novel algorithm based solely on network topology, that can be used to align any two networks. We apply it to biological networks to produce by far the most complete topological alignments of biological networks to date. We demonstrate that both species phylogeny and detailed biological function of individual proteins can be extracted from our alignments. Topology-based alignments have the potential to provide a completely new, independent source of phylogenetic information. Our alignment of the protein-protein interaction networks of two very different species-yeast and human-indicate that even distant species share a surprising amount of network topology, suggesting broad similarities in internal cellular wiring across all life on Earth.

Indexed as

AlgorithmsModels, BiologicalPhylogenyComputational BiologyHumansProteinsSaccharomyces cerevisiaeSaccharomyces cerevisiae ProteinsProteinsSaccharomyces cerevisiae Proteins

Identifiers

PMID20236959
PMCPMC2894889

What OpenQuestion holds

Textmetadata
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.