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.

Details

Title
Integrated intra‐ and intercellular signaling knowledge for multicellular omics analysis
Author
Türei, Dénes 1   VIAFID ORCID Logo  ; Valdeolivas, Alberto 1   VIAFID ORCID Logo  ; Gul, Lejla 2 ; Nicolàs Palacio‐Escat 3   VIAFID ORCID Logo  ; Klein, Michal 4   VIAFID ORCID Logo  ; Ivanova, Olga 1   VIAFID ORCID Logo  ; Ölbei, Márton 5   VIAFID ORCID Logo  ; Gábor, Attila 1   VIAFID ORCID Logo  ; Theis, Fabian 6   VIAFID ORCID Logo  ; Módos, Dezső 5   VIAFID ORCID Logo  ; Korcsmáros, Tamás 5   VIAFID ORCID Logo  ; Julio Saez‐Rodriguez 7   VIAFID ORCID Logo 

 Faculty of Medicine and Heidelberg University Hospital, Institute of Computational Biomedicine, Heidelberg University, Heidelberg, Germany 
 Earlham Institute, Norwich, UK 
 Faculty of Medicine and Heidelberg University Hospital, Institute of Computational Biomedicine, Heidelberg University, Heidelberg, Germany; Faculty of Medicine, Joint Research Centre for Computational Biomedicine (JRC‐COMBINE), RWTH Aachen University, Aachen, Germany; Faculty of Biosciences, Heidelberg University, Heidelberg, Germany 
 Institute of Computational Biology, Helmholtz Zentrum München, Neuherberg, Germany 
 Earlham Institute, Norwich, UK; Quadram Institute Bioscience, Norwich, UK 
 Institute of Computational Biology, Helmholtz Zentrum München, Neuherberg, Germany; Department of Mathematics, Technical University of Munich, Garching, Germany 
 Faculty of Medicine and Heidelberg University Hospital, Institute of Computational Biomedicine, Heidelberg University, Heidelberg, Germany; Faculty of Medicine, Joint Research Centre for Computational Biomedicine (JRC‐COMBINE), RWTH Aachen University, Aachen, Germany 
Section
Articles
Publication year
2021
Publication date
Mar 2021
Publisher
EMBO Press
e-ISSN
17444292
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2506671864
Copyright
© 2021. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.