Evidence map›Paper›PMID 34634810›Full record

ArticleNucleic acids research2022

SignaLink3: a multi-layered resource to uncover tissue-specific signaling networks.

Luca Csabai, Dávid Fazekas, Tamás Kadlecsik, Máté Szalay-Bekő, Balázs Bohár, Matthew Madgwick, Dezső Módos, Márton Ölbei, Lejla Gul, Padhmanand Sudhakar and 19 more

Abstract read
In one paragraph

Article in Nucleic acids research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing 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

28 citing papers in PubMed.

  1. CanInternational journal of molecular sciences · 2026
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  3. Review
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  5. Article
  6. Using Biological Networks to Guide Biomedical Prediction.Methods in molecular biology (Clifton, N.J.) · 2026
    Article
  7. Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. The zebrafish (NAR genomics and bioinformatics · 2025
    Article
  13. Review
  14. Article
  15. Article
  16. Augusta: From RNA-Seq to gene regulatory networks and Boolean models.Computational and structural biotechnology journal · 2024
    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

29 authors.

Luca CsabaiEarlham Institute, Norwich NR4 7UZ, UK.
Dávid FazekasEarlham Institute, Norwich NR4 7UZ, UK.
Tamás KadlecsikDepartment of Genetics, ELTE Eötvös Loránd University, Budapest H-1117, Hungary.
Máté Szalay-BekőEarlham Institute, Norwich NR4 7UZ, UK.
Balázs BohárEarlham Institute, Norwich NR4 7UZ, UK.
Matthew MadgwickEarlham Institute, Norwich NR4 7UZ, UK.
Dezső MódosEarlham Institute, Norwich NR4 7UZ, UK.
Márton ÖlbeiEarlham Institute, Norwich NR4 7UZ, UK.
Lejla GulEarlham Institute, Norwich NR4 7UZ, UK.
Padhmanand SudhakarEarlham Institute, Norwich NR4 7UZ, UK.
János KubischDepartment of Genetics, ELTE Eötvös Loránd University, Budapest H-1117, Hungary.
Oyebode James OyeyemiZeekay Institute of Advanced and Professional Studies, Lagos, Nigeria.
Orsolya LiskaDepartment of Genetics, ELTE Eötvös Loránd University, Budapest H-1117, Hungary.
Eszter AriDepartment of Genetics, ELTE Eötvös Loránd University, Budapest H-1117, Hungary.
Bernadette HotziDepartment of Genetics, ELTE Eötvös Loránd University, Budapest H-1117, Hungary.
Viktor A BillesDepartment of Genetics, ELTE Eötvös Loránd University, Budapest H-1117, Hungary.
Eszter MolnárDepartment of Genetics, ELTE Eötvös Loránd University, Budapest H-1117, Hungary.
László Földvári-NagyDepartment of Genetics, ELTE Eötvös Loránd University, Budapest H-1117, Hungary.
Kitti CsályiDepartment of Genetics, ELTE Eötvös Loránd University, Budapest H-1117, Hungary.
Amanda DemeterEarlham Institute, Norwich NR4 7UZ, UK.
Nóra PápaiDepartment of Genetics, ELTE Eötvös Loránd University, Budapest H-1117, Hungary.
Mihály KoltaiCentre for the Mathematical Modelling of Infectious Diseases (CMMID), London School of Hygiene & Tropical Medicine, London WC1E 7HT, UK.
Máté VargaDepartment of Genetics, ELTE Eötvös Loránd University, Budapest H-1117, Hungary.
Katalin LentiDepartment of Morphology and Physiology, Semmelweis University, Budapest H-1088, Hungary.
Illés J FarkasCitibank Europe plc Hungarian Branch Office, Budapest H-1133, Hungary.
Dénes TüreiHeidelberg University, Faculty of Medicine, and Heidelberg University Hospital, Institute for Computational Biomedicine, Bioquant, Heidelberg, Germany.
Péter CsermelyDepartment of Molecular Biology, Semmelweis University, Budapest H-1094, Hungary.
Tibor VellaiDepartment of Genetics, ELTE Eötvös Loránd University, Budapest H-1117, Hungary.
Tamás KorcsmárosEarlham Institute, Norwich NR4 7UZ, UK.ORCID 0000-0003-1717-996X

Funding

Biotechnology and Biological Sciences Research Council BB/CCG1720/1Biotechnology and Biological Sciences Research Council BB/M011216/1Biotechnology and Biological Sciences Research Council BB/R012490/1Biotechnology and Biological Sciences Research Council BB/S50743X/1Biotechnology and Biological Sciences Research Council BBS/E/F/000PR10353Biotechnology and Biological Sciences Research Council BBS/E/F/000PR10355Biotechnology and Biological Sciences Research Council BBS/E/T/000PR9814Biotechnology and Biological Sciences Research Council BBS/E/T/000PR9817Biotechnology and Biological Sciences Research Council BBS/E/T/000PR9819European Research Council 694679
6 · The paper itself

Abstract

Signaling networks represent the molecular mechanisms controlling a cell's response to various internal or external stimuli. Most currently available signaling databases contain only a part of the complex network of intertwining pathways, leaving out key interactions or processes. Hence, we have developed SignaLink3 (http://signalink.org/), a value-added knowledge-base that provides manually curated data on signaling pathways and integrated data from several types of databases (interaction, regulation, localisation, disease, etc.) for humans, and three major animal model organisms. SignaLink3 contains over 400 000 newly added human protein-protein interactions resulting in a total of 700 000 interactions for Homo sapiens, making it one of the largest integrated signaling network resources. Next to H. sapiens, SignaLink3 is the only current signaling network resource to provide regulatory information for the model species Caenorhabditis elegans and Danio rerio, and the largest resource for Drosophila melanogaster. Compared to previous versions, we have integrated gene expression data as well as subcellular localization of the interactors, therefore uniquely allowing tissue-, or compartment-specific pathway interaction analysis to create more accurate models. Data is freely available for download in widely used formats, including CSV, PSI-MI TAB or SQL.

Indexed as

Databases, GeneticAnimalsCaenorhabditis elegansDrosophila melanogasterGene Regulatory NetworksHumansProtein Interaction MapsSignal TransductionZebrafish

Identifiers

PMID34634810
PMCPMC8728204

What OpenQuestion holds

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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.