Evidence map›Paper›PMID 26681426›Full record

ReviewMolecular systems biology2015

Fundamentals of protein interaction network mapping.

Jamie Snider, Max Kotlyar, Punit Saraon, Zhong Yao, Igor Jurisica, Igor Stagljar

Abstract readReview
In one paragraph

Review in Molecular systems biology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 143 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
143citing papers in PubMed, 2 pooled it
–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

143 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Article
  10. Article
  11. Review
  12. Predicting Protein-Protein Interactions from Machine-Learned Representations.Advances in experimental medicine and biology · 2026
    Review
  13. Protein-Protein Interactions with the Fragment Molecular Orbital Method.Methods in molecular biology (Clifton, N.J.) · 2026
    Article
  14. Review
  15. Article
  16. Article
  17. Review
  18. Article
  19. Review
  20. Review

83 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

6 authors.

Jamie SniderDonnelly Centre, Department of Biochemistry, Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada.
Max KotlyarPrincess Margaret Cancer Center, IBM Life Sciences Discovery Centre, University Health Network, Ontario, Canada.
Punit SaraonDonnelly Centre, Department of Biochemistry, Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada.
Zhong YaoDonnelly Centre, Department of Biochemistry, Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada.
Igor JurisicaPrincess Margaret Cancer Center, IBM Life Sciences Discovery Centre, University Health Network, Ontario, Canada.
Igor StagljarDonnelly Centre, Department of Biochemistry, Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada igor.stagljar@utoronto.ca.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Studying protein interaction networks of all proteins in an organism ("interactomes") remains one of the major challenges in modern biomedicine. Such information is crucial to understanding cellular pathways and developing effective therapies for the treatment of human diseases. Over the past two decades, diverse biochemical, genetic, and cell biological methods have been developed to map interactomes. In this review, we highlight basic principles of interactome mapping. Specifically, we discuss the strengths and weaknesses of individual assays, how to select a method appropriate for the problem being studied, and provide general guidelines for carrying out the necessary follow-up analyses. In addition, we discuss computational methods to predict, map, and visualize interactomes, and provide a summary of some of the most important interactome resources. We hope that this review serves as both a useful overview of the field and a guide to help more scientists actively employ these powerful approaches in their research.

Indexed as

AnimalsComputational BiologyHumansMammalsProtein Interaction MappingProtein Interaction MapsProteinsProteinsbioinformaticsinteractome mappingPPI technologiesprotein‐protein interactions (PPIs)proteomics

Identifiers

PMID26681426
PMCPMC4704491

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.