Molecular Systems BiologySystems BiologyPeer-reviewed journal article
Integrated intra- and intercellular signaling knowledge for multicelullar omics analysis
Dénes TüreiiD, Alberto ValdeolivasiD, Lejla GuliD, Nicolàs Palacio‐EscatiD, Michal KleiniD, Olga IvanovaiD, Marton L. OlbeiiD, Attila GáboriD, Fabian Joachim TheisiD, Dezső MódosiD, Tamas Douglas KorcsmarosiD, Julio Sáez-RodrígueziD
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Abstract
Molecular knowledge of biological processes is a cornerstone in the analysis of omics data. Applied to single-cell data, such analyses can provide mechanistic insights into individual cells and their interactions. However, knowledge of intercellular communication is scarce, scattered across different resources, and not linked to intracellular processes. To address this gap, we combined over 100 resources in a single database. It covers the interactions and roles of proteins in inter- and intracellular signal transduction, as well as transcriptional and post-transcriptional regulation. We also provide a comprehensive collection of protein complexes and rich annotations on the properties of proteins, including function, localization, and role in diseases. The resource is available for human, and via homology translation for mouse and rat. The data is accessible via OmniPaths web service, a Cytoscape plugin, and packages in R/Bioconductor and Python, providing convenient access options for both computational and experimental scientists. Our resource provides a single access point to knowledge spanning intra- and intercellular processes for data analysis, as we demonstrate in applications to study SARS-CoV-2 infection and ulcerative colitis. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=92 SRC="FIGDIR/small/221242v2_ufig1.gif" ALT="Figure 1"> View larger version (17K): org.highwire.dtl.DTLVardef@15de883org.highwire.dtl.DTLVardef@4bfb6aorg.highwire.dtl.DTLVardef@67113aorg.highwire.dtl.DTLVardef@9c328a_HPS_FORMAT_FIGEXP M_FIG C_FIG
- organism: human
- organism: mouse
- organism: rat
- assay: protein sequence
- assay: protein structure
- research focus: database / resource
- approach: statistical model
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