Evidence map›Paper›PMID 28194172›Full record

ArticleEURASIP journal on bioinformatics & systems biology2015

The post-genomic era of biological network alignment.

Fazle E Faisal, Lei Meng, Joseph Crawford, Tijana Milenković

Abstract read
In one paragraph

Article in EURASIP journal on bioinformatics & systems biology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing 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

24 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Pairwise Biological Network Alignment Based on Discrete Bat Algorithm.Computational and mathematical methods in medicine · 2021
    Article
  10. Review
  11. Article
  12. Pairwise Versus Multiple Global Network Alignment.IEEE access : practical innovations, open solutions · 2020
    Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. graphkernels: R and Python packages for graph comparison.Bioinformatics (Oxford, England) · 2018
    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

4 authors.

Fazle E FaisalDepartment of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN, 46556 USA ; Interdisciplinary Center for Network Science and Applications, University of Notre Dame, Notre Dame, IN, 46556 USA ; ECK Institute for Global Health, University of Notre Dame, Notre Dame, IN, 46556 USA.
Lei MengDepartment of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN, 46556 USA.
Joseph CrawfordDepartment of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN, 46556 USA ; Interdisciplinary Center for Network Science and Applications, University of Notre Dame, Notre Dame, IN, 46556 USA ; ECK Institute for Global Health, University of Notre Dame, Notre Dame, IN, 46556 USA.
Tijana MilenkovićDepartment of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN, 46556 USA ; Interdisciplinary Center for Network Science and Applications, University of Notre Dame, Notre Dame, IN, 46556 USA ; ECK Institute for Global Health, University of Notre Dame, Notre Dame, IN, 46556 USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Biological network alignment aims to find regions of topological and functional (dis)similarities between molecular networks of different species. Then, network alignment can guide the transfer of biological knowledge from well-studied model species to less well-studied species between conserved (aligned) network regions, thus complementing valuable insights that have already been provided by genomic sequence alignment. Here, we review computational challenges behind the network alignment problem, existing approaches for solving the problem, ways of evaluating their alignment quality, and the approaches' biomedical applications. We discuss recent innovative efforts of improving the existing view of network alignment. We conclude with open research questions in comparative biological network research that could further our understanding of principles of life, evolution, disease, and therapeutics.

Indexed as

Across-species knowledge transferAgingBiological network researchFunctional orthologyNetwork alignmentProtein-protein interactions

Identifiers

PMID28194172
PMCPMC5270500

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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.