Evidence map›Paper›PMID 33749993›Full record

ArticleMolecular systems biology2021

Integrated intra- and intercellular signaling knowledge for multicellular omics analysis.

Dénes Türei, Alberto Valdeolivas, Lejla Gul, Nicolàs Palacio-Escat, Michal Klein, Olga Ivanova, Márton Ölbei, Attila Gábor, Fabian Theis, Dezső Módos and 2 more

Abstract read
In one paragraph

Article in Molecular systems biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 219 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
219citing 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

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

  1. Pooled it
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  16. PD-1/PD-L1 Signaling in Non-ICI Myocarditis.JACC. Basic to translational science · 2026
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  18. Review
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159 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

12 authors.

Dénes TüreiFaculty of Medicine and Heidelberg University Hospital, Institute of Computational Biomedicine, Heidelberg University, Heidelberg, Germany.ORCID 0000-0002-7249-9379
Alberto ValdeolivasFaculty of Medicine and Heidelberg University Hospital, Institute of Computational Biomedicine, Heidelberg University, Heidelberg, Germany.ORCID 0000-0001-5482-9023
Lejla GulEarlham Institute, Norwich, UK.
Nicolàs Palacio-EscatFaculty of Medicine and Heidelberg University Hospital, Institute of Computational Biomedicine, Heidelberg University, Heidelberg, Germany.ORCID 0000-0002-7022-1437
Michal KleinInstitute of Computational Biology, Helmholtz Zentrum München, Neuherberg, Germany.ORCID 0000-0002-2433-6380
Olga IvanovaFaculty of Medicine and Heidelberg University Hospital, Institute of Computational Biomedicine, Heidelberg University, Heidelberg, Germany.ORCID 0000-0002-9111-4593
Márton ÖlbeiEarlham Institute, Norwich, UK.ORCID 0000-0002-4903-6237
Attila GáborFaculty of Medicine and Heidelberg University Hospital, Institute of Computational Biomedicine, Heidelberg University, Heidelberg, Germany.ORCID 0000-0002-0776-1182
Fabian TheisInstitute of Computational Biology, Helmholtz Zentrum München, Neuherberg, Germany.ORCID 0000-0002-2419-1943
Dezső MódosEarlham Institute, Norwich, UK.ORCID 0000-0001-9412-6867
Tamás KorcsmárosEarlham Institute, Norwich, UK.ORCID 0000-0003-1717-996X
Julio Saez-RodriguezFaculty of Medicine and Heidelberg University Hospital, Institute of Computational Biomedicine, Heidelberg University, Heidelberg, Germany.ORCID 0000-0002-8552-8976

Funding

Biotechnology and Biological Sciences Research Council BB/J004529/1Biotechnology and Biological Sciences Research Council BBS/E/F/000PR10355Biotechnology and Biological Sciences Research Council BBS/E/T/000PR9817Deutsche Forschungsgemeinschaft (DFG) SA 3554/1-2European Union Innovative Medicines Initiative TransQST 116030Federal Ministry of Education (BMFB, Computational Life Sciences grant) 031L0181BJRC COMBINE, partially funded by Bayer AGUK Research and Innovation|Biotechnology and Biological Sciences Research Council, ISP grant for Gut Microbes and Health BB/R012490/1UK Research and Innovation|Biotechnology and Biological Sciences Research Council, Norwich Research Park Biosciences Doctoral Training Partnership grant BB/M011216/1UKRI|Biotechnology and Biological Sciences Research Council (BBSRC) BB/CSP17270/1UKRI|Biotechnology and Biological Sciences Research Council (BBSRC) BB/J004529/1UKRI|Biotechnology and Biological Sciences Research Council (BBSRC) BB/P016774/1
6 · The paper itself

Abstract

Molecular knowledge of biological processes is a cornerstone in omics data analysis. Applied to single-cell data, such analyses provide mechanistic insights into individual cells and their interactions. However, knowledge of intercellular communication is scarce, scattered across resources, and not linked to intracellular processes. To address this gap, we combined over 100 resources covering interactions and roles of proteins in inter- and intracellular signaling, as well as transcriptional and post-transcriptional regulation. We added protein complex information and annotations on function, localization, and role in diseases for each protein. The resource is available for human, and via homology translation for mouse and rat. The data are accessible via OmniPath's web service (https://omnipathdb.org/), a Cytoscape plug-in, and packages in R/Bioconductor and Python, providing access options for computational and experimental scientists. We created workflows with tutorials to facilitate the analysis of cell-cell interactions and affected downstream intracellular signaling processes. OmniPath provides a single access point to knowledge spanning intra- and intercellular processes for data analysis, as we demonstrate in applications studying SARS-CoV-2 infection and ulcerative colitis.

Indexed as

Signal TransductionAnimalsCell CommunicationColitis, UlcerativeComputational BiologyCOVID-19Databases, FactualEnzymesHumansMiceProtein Processing, Post-TranslationalProteinsRatsSingle-Cell AnalysisSoftwareWorkflowEnzymesProteinsintercellular signalingligand-receptor interactionsomics integrationpathwayssignaling network

Identifiers

PMID33749993
PMCPMC7983032

What Socratic 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 Socratic graph.