OmniPath
@omnipathdb
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OmniPath: molecular biology knowledge from 100+ databases
Heidelberg, Germany
Joined October 2017
RT @saezlab: Building a knowledge graph for biomedical tasks usually takes months or years. 😰 What if you could do it in weeks or days? 🏃 W….
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Check out LIANA that uses @omnipathdb to systematically compare and combine resources & methods to study cell-cell communication from #scRNA.
We are 🥳 to share that a substantially improved version of LIANA’s manuscript "Comparison of Resources and Methods to infer Cell-Cell Communication from Single-cell RNA Data" has now been published at: Highlights for some of our findings in the 🧵1/10
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RT @saezlab: We have also added several tutorials showing how to use decoupler and @omnipathdb in single cell analyses such as automatic ce….
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RT @saezlab: We are looking for PostDosc/ PhDs in Medical Bioinformatics & Machine Learning @uniklinik_hd @UniHeidelberg #multiomics #singl….
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Check MISTy from @tanevski et al @saezlab to analyze spatial omics - they used @omnipathdb 's annotated prior knowledge to link intracellular pathway activities & the expression of ligands in space 👇.
Play MISTy for me, says someone with spatial omics data to find relationships between markers in. It's a machine learning method from @tanevski, @saezlab & co. It's demonstrated on mass cytometry and spatial transcriptomics data from breast cancer
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RT @saezlab: Our updated manuscript describing methods for bioactivity inference (pathways, TFs, etc.) is now published in @BioinfoAdv http….
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The great spatial omics platform from @fabian_theis group is out in @naturemethods 🥳 Squidpy uses OmniPath data for ligand-receptor interactions 🤩 Special thanks to Michal Klein for implementing the OmniPath Python client✌️.
Interested in spatial omics? Plz check out our squidpy tool, bringing together omics & image analysis to enable a scalable description of spatial molecular data. Out today @naturemethods thx to @g_palla1, @HannahSpitzer1 & team!
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Our paper is among the 8 most read in @MolSystBiol and got already 27 citations! 🎉 In @saezlab & @KorcsmarosLab it's a great pleasure for us to see you using our work. Meanwhile we are preparing big new developments, stay tuned 😉
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RT @saezlab: Check out #COVID19 Disease Map Consortia .@CovidPathways knowledge repository great community effort….
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We just talked about OmnipathR at BioC2021 @Bioconductor, many thanks to all the participants and the organizers! 🌞 Slides: Vignette (and further materials): Other @saezlab tools:
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6,225 new protein complexes in OmniPath thanks to 2.0 from @kdrew @jbwallingford & @edward_marcotte 🖥️ 🏡 📰
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Human Cell Map from @gingraslab1 is available in OmniPath! ⭐️ Subcellular localization of 6,000+ proteins from a BioID screen in HEK cells:
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Estimate ligand activities from #transcriptomics with the new OmniPath-NicheNet workflow 🤩 🤩 Customizable networks from OmniPath & other resources + NicheNet algorithm from @RobinBrowaeys of @saeyslab
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RT @humzalikhan: Check out my first first-author work with @ManishButte! We used @omnipathdb, a protein interactions meta-database, as well….
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Happy that @omnipathdb was helpful as a meta-resource of cell-cell interaction resources in this comparison of methods to estimate cell-cell communication from scRNA-seq data.
There are many tools and resources to estimate Cell-Cell Communication from scRNA data - do you wonder which one you should use? We do too! To find out, we compared 6 methods and 15 resources
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Access OmniPath from R Python and @cytoscape or build your own database by pypath - and send us feedback and suggestions.
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OmniPath provides prior knowledge for many omics analysis and modeling tools, including a close integration with NicheNet @saeyslab to infer ligand activities from transcriptomics and the single-cell platforms squidpy + @scanpy_team @fabian_theis
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Our case studies about autocrine signaling in #SARS_CoV_2 infected Calu3 cells @alvaldeolivas and myofibroblast-Treg cell signaling in #IBD (ulcerative colitis) with @KorcsmarosLab show how OmniPath helps to analyze intercellular communication
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Protein function, disease role, tissue expression, localization, structure and more in the annotations database from 50 resources
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