Evidence map›Paper›PMID 32707033›Full record

ArticleMolecular cell2020

Kinase Interaction Network Expands Functional and Disease Roles of Human Kinases.

Marija Buljan, Rodolfo Ciuffa, Audrey van Drogen, Anton Vichalkovski, Martin Mehnert, George Rosenberger, Sohyon Lee, Markku Varjosalo, Lucia Espona Pernas, Vincent Spegg and 3 more

Open access · bronzeAbstract read
In one paragraph

Article in Molecular cell, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 69 papers.

0numbers the graph read from it
0cells of the map it votes in
69citing papers in PubMed
5.4field-weighted citation impact, top 3% 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

69 citing papers in PubMed, 126 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. A Constellation of Fluorescent Biosensors to Illuminate the Galaxy of Protein Kinases.Chembiochem : a European journal of chemical biology · 2026
    Review
  5. Article
  6. Review
  7. Article
  8. Article
  9. Article
  10. Article
  11. Case Report: Expanding theFrontiers in pediatrics · 2026
    Article
  12. Article
  13. Article
  14. Article
  15. Integrative Transcriptomic and Proteomic Analysis RevealsAnimals : an open access journal from MDPI · 2025
    Article
  16. Article
  17. Article
  18. Article
  19. Review
  20. Article

9 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

13 authors at 3 institutions in 3 countries.

Marija BuljanInstitute of Molecular Systems Biology, ETH Zurich, 8093 Zurich, Switzerland; Empa, Swiss Federal Laboratories for Materials Science and Technology, 9014 St. Gallen, Switzerland.
Rodolfo CiuffaInstitute of Molecular Systems Biology, ETH Zurich, 8093 Zurich, Switzerland.
Audrey van DrogenInstitute of Molecular Systems Biology, ETH Zurich, 8093 Zurich, Switzerland.
Anton VichalkovskiInstitute of Molecular Systems Biology, ETH Zurich, 8093 Zurich, Switzerland.
Martin MehnertInstitute of Molecular Systems Biology, ETH Zurich, 8093 Zurich, Switzerland.
George RosenbergerInstitute of Molecular Systems Biology, ETH Zurich, 8093 Zurich, Switzerland; Columbia University Department of Systems Biology, New York, NY 10032, USA.
Sohyon LeeInstitute of Molecular Systems Biology, ETH Zurich, 8093 Zurich, Switzerland.
Markku VarjosaloInstitute of Biotechnology, University of Helsinki, Helsinki 00014, Finland.
Lucia Espona PernasInstitute of Molecular Systems Biology, ETH Zurich, 8093 Zurich, Switzerland.
Vincent SpeggDepartment of Molecular Mechanisms of Disease, University of Zurich, 8057 Zurich, Switzerland.
Berend SnijderInstitute of Molecular Systems Biology, ETH Zurich, 8093 Zurich, Switzerland.
Ruedi AebersoldInstitute of Molecular Systems Biology, ETH Zurich, 8093 Zurich, Switzerland; Faculty of Science, University of Zurich, Zurich, Switzerland. Electronic address: aebersold@imsb.biol.ethz.ch.
Matthias GstaigerInstitute of Molecular Systems Biology, ETH Zurich, 8093 Zurich, Switzerland. Electronic address: matthias.gstaiger@imsb.biol.eth.ch.
ETH Zurich · CHUniversity of Zurich · CHUniversity of Helsinki · FI

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Protein kinases are essential for signal transduction and control of most cellular processes, including metabolism, membrane transport, motility, and cell cycle. Despite the critical role of kinases in cells and their strong association with diseases, good coverage of their interactions is available for only a fraction of the 535 human kinases. Here, we present a comprehensive mass-spectrometry-based analysis of a human kinase interaction network covering more than 300 kinases. The interaction dataset is a high-quality resource with more than 5,000 previously unreported interactions. We extensively characterized the obtained network and were able to identify previously described, as well as predict new, kinase functional associations, including those of the less well-studied kinases PIM3 and protein O-mannose kinase (POMK). Importantly, the presented interaction map is a valuable resource for assisting biomedical studies. We uncover dozens of kinase-disease associations spanning from genetic disorders to complex diseases, including cancer.

Indexed as

Gene Regulatory NetworksComputational BiologyDatasets as TopicGene Expression RegulationGene OntologyGenetic Diseases, InbornHumansMetabolic Networks and PathwaysMolecular Sequence AnnotationMuscular DystrophiesNeoplasmsNeurodegenerative DiseasesProtein Interaction MappingProtein KinasesProtein Serine-Threonine KinasesProto-Oncogene ProteinsPIM3 protein, humanPOMK protein, humanProtein KinasesProtein Serine-Threonine KinasesProto-Oncogene Proteinscancerdisease moduleinteraction networkkinomeprotein complexesprotein kinasesproteomicssignaling regulationsystems biology

Identifiers

PMID32707033
PMCPMC7427327
OpenAlexW3044562385

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.