Knowledge Representation and Computational Reasoning for Precision Medicine Analytics
This event is in the past.
Detroit, MI 48201
Effective utilization of omics-derived knowledge is crucial for realization of precision medicine ideas. Integrative software tools with greater explanatory power that can lead to actionable outcomes are needed to enable physicians practice precision medicine. In this talk we will discuss knowledge representation and computational reasoning methods that can effectively manage biomedical knowledge to bring about actionable outcomes in personalized diagnostics and therapeutics. To this end, we have been investigating advanced inference methods to map clinical biomarkers data to biological pathways to recreate interplay of signaling proteomic networks for individualized patient cases. Our computational formalism called Resource Description Framework (RDF)-induced Influgrams (RIIG) has been shown in a recent proof-of-concept study to exhibit qualities to provide patient-specific reasoning in cancer cases. RIIG takes advantage of vast amounts of publicly available curated biological knowledge represented in RDF format and introduces the notions of RDF relevance and RDF colliders, which mimic conditional independence and “explaining away” mechanisms of probabilistic systems, respectively. Using these constructs RIIG can uncover complex relationships among biological entities and enable effective management of knowledge granularity and causality for precision medicine analytics. We will also discuss bioinformatics methods for the reduction of complexity of biomedical knowledge and application of graph algorithms over “flexible” computable knowledge.
Dr. Shin studies computational methods in biomedicine. He received his Master’s degree in Computer Science from Moscow State University of Computer Science, and PhD in Biomedical Informatics from University of Missouri. Dr. Shin then joined faculty in the University of Missouri where he now leads the Translational and Cancer Bioinformatics research laboratory. He also serves as Director of the Division of Pathology Informatics in the MU School of Medicine. Under his leadership, new computer systems have been designed, implemented and supported, including anti-nuclear antibody, flow cytometry, bone marrow, molecular pathology laboratory information systems and biorepository software, pathology digital dictation system, and high definition microscopy telepathology system. Dr. Shin has also established and leads the Digital Pathology laboratory, which conducts research in biomedical imaging informatics using Whole Slide Imaging technology and provides services for researchers and medical practitioners.