A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical ReportsAlexander R. Pelletier 1,2,3, Dylan Steinecke 1,3,4, Dibakar Sigdel 1, Irsyad Adam 1, J. Harry Caufield 1, Vladimir Guevara-Gonzalez 1, Joseph Ramirez 1, Aarushi Verma 1, Kaitlyn Bali 1, Katherine Downs 1, Wei Wang 1,2,3, Alex Bui 3,4, Peipei Ping 1,2,3,4,5
1Department of Physiology, UCLA School of Medicine, 2Scalable Analytics Institute (ScAi) at Department of Computer Science, UCLA School of Engineering, 3NIH BRIDGE2AI Center at UCLA & NHLBI Integrated Cardiovascular Data Science Training Program, UCLA, 4Medical Informatics, University of California at Los Angeles (UCLA), 5Department of Medicine (Cardiology), UCLA School of Medicine
A computational protocol, CaseOLAP LIFT, and a use case are presented for investigating mitochondrial proteins and their associations with cardiovascular disease as described in biomedical reports. This protocol can be easily adapted to study user-selected cellular components and diseases.
