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Norway

Join dkNET Webinar: The Signaling Pathways Project: Putting The R In FAIR Data on Friday, April 26, 2019 at 11am PDT

Join dkNET Webinar: The Signaling Pathways Project: Putting The R In FAIR Data on Friday, April 26, 2019 at 11am PDT

*Watch recorded webinar here: https://youtu.be/gGBDMqBhfhQ

*Webinar slides: https://www.slideshare.net/dkNET/dknet-webinar-the-signaling-pathways-project-putting-the-r-in-fair-data-04262019


Join dkNET Webinar on Friday, April 26, 2019, 11am - 12pm (PDT)

Public transcriptomic and ChIP-Seq datasets have the potential to illuminate facets of transcriptional regulation by mammalian cellular signaling pathways not yet explored in the research literature. Unfortunately, a variety of obstacles prevent routine re-use of these datasets by bench biologists for hypothesis generation and data validation. We have designed a web knowledgebase, the Signaling Pathways Project (SPP), which incorporates stable community classifications of three major categories of cellular signaling pathway node (receptors, enzymes and transcription factors) and the bioactive small molecules (BSMs) known to modulate their functions. We then subjected over 10,000 publically archived transcriptomic or ChIP-Seq experiments to a biocuration pipeline that mapped them to their relevant signaling pathway node, BSM or biosample (tissue or cell line of study). To provide for prediction of pathway node-target transcriptional regulatory relationships, we generated consensus ‘omics signatures, or consensomes, based on the significant differential expression or promoter occupancy of genomic targets across all underlying transcriptomic (expression array and RNA-Seq) or ChIP-Seq experiments. To expose the SPP knowledgebase to biology researchers, we designed a web browser interface that accommodates a variety of routine data mining strategies to identify node-gene target regulatory relationships previously uncharacterized in the research literature. SPP will power the Hypothesis Center of dkNET 3.0.


Dial-in information:   https://uchealth.zoom.us/meeting/register/343467d5d80b4324d746f627e8486654


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