Join dkNET Webinar: The Signaling Pathways Project, an integrated ‘omics knowledgebase for mammalian cellular signaling pathways on Friday, November 22, 2019 at 11am PST

*Watch recorded webinar here: https://youtu.be/hC_aZ3opYcA
*Webinar slides: https://www.slideshare.net/dkNET/dknet-webinar-the-signaling-pathways-project-an-integrated-omics-knowledgebase-for-mammalian-cellular-signaling-pathways-11222019

Join dkNET Webinar on Friday, November 22, 2019, 11am - 12pm (PST)

Mining of integrated public transcriptomic and ChIP-Seq (cistromic) datasets can illuminate functions of mammalian cellular signaling pathways not yet explored in the research literature. Here, we designed a web knowledgebase, the Signaling Pathways Project (SPP), which incorporates community classifications of signaling pathway nodes (receptors, enzymes, transcription factors and co-nodes) and their cognate bioactive small molecules. We then mapped over 10,000 public transcriptomic or cistromic experiments to their pathway node or biosample of study. To enable prediction of pathway node-gene target transcriptional regulatory relationships through SPP, we generated consensus ‘omics signatures, or consensomes, which ranked genes based on measures of their significant differential expression or promoter occupancy across transcriptomic or cistromic experiments mapped to a specific node family. Consensomes were validated using alignment with canonical literature knowledge, gene target-level integration of transcriptomic and cistromic data points, and in bench experiments confirming previously uncharacterized node-gene target regulatory relationships. To expose the SPP knowledgebase to researchers, a web browser interface was designed that accommodates numerous routine data mining strategies. SPP is freely accessible at https://www.signalingpathways.org. In this webinar, the presenters will demonstrate several SPP use cases, as well as take questions from the audience about specific aspects of SPP. SPP will power the Hypothesis Center of dkNET 3.0.  

Dial-in information:   https://uchealth.zoom.us/meeting/register/837179770adf7fbddc2040ba88984b7b