The Signaling Pathways Project, an integrated 'omics knowledgebase for mammalian cellular signaling pathways.

Journal Article (Journal Article)

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 .

Full Text

Duke Authors

Cited Authors

  • Ochsner, SA; Abraham, D; Martin, K; Ding, W; McOwiti, A; Kankanamge, W; Wang, Z; Andreano, K; Hamilton, RA; Chen, Y; Hamilton, A; Gantner, ML; Dehart, M; Qu, S; Hilsenbeck, SG; Becnel, LB; Bridges, D; Ma'ayan, A; Huss, JM; Stossi, F; Foulds, CE; Kralli, A; McDonnell, DP; McKenna, NJ

Published Date

  • October 31, 2019

Published In

Volume / Issue

  • 6 / 1

Start / End Page

  • 252 -

PubMed ID

  • 31672983

Pubmed Central ID

  • PMC6823428

Electronic International Standard Serial Number (EISSN)

  • 2052-4463

International Standard Serial Number (ISSN)

  • 2052-4463

Digital Object Identifier (DOI)

  • 10.1038/s41597-019-0193-4

Language

  • eng