Abstract: Pathway-based analysis holds promise to be instrumental in precision and personalized medicine analytics. However, the majority of pathway-based analysis methods utilize “fixed” or “rigid” data sets that limit their ability to account for complex biological inter-dependencies. Here, we present REDESIGN: RDF-based Differential Signaling Pathway informatics framework. The distinctive feature of the REDESIGN is that it is designed to run on “flexible” ontology-enabled data sets of curated signal transduction pathway maps to uncover high explanatory differential pathway mechanisms on gene-to-gene level. The experiments on two morphoproteomic cases demonstrated REDESIGN’s capability to generate actionable hypotheses in precision/personalized medicine analytics.

Learning Objective 1: To learn pathway analytics methods based on flexible ontology-driven data sets


Zainab Al-Taie (Presenter)
University of Missouri

Nattapon Thanintorn, University of Missouri
Ilker Ersoy, University of Missouri
Olha Kholod, University of Missouri
Kristen Taylor, University of Missouri
Richard Hammer, University of Missouri
Dmitriy Shin, University of Missouri

Presentation Materials: