BEGIN:VCALENDAR VERSION:2.0 PRODID:icalendar-ruby CALSCALE:GREGORIAN X-WR-CALNAME:Final Doctoral Defense for Md Asad Rahman X-WR-TIMEZONE:Central Time (US & Canada) BEGIN:VEVENT DTSTAMP:20260611T113727Z UID:tag:localist.com\,2008:EventInstance_46828312853769 DTSTART:20240708T140000Z DTEND:20240708T153000Z DESCRIPTION:Md Asad Rahman\, a doctoral candidate in systems engineering\, will defend their dissertation titled “A Bayesian Inference Based Comple x Systems Approach in Precision Medicine.” Asad’s advisor\, Dr. Jinlin g Liu\, is an advisor in the engineering management and systems engineerin g department. The dissertation abstract is provided below.\n\nPrecision me dicine\, tailoring healthcare based on individual genetic profiles\, repre sents a fundamental shift from traditional medical approaches. This disser tation introduces a novel and personalized framework\, including advanced genomic tools\, the Individualized Bayesian Inference (IBI)\, and the Indi vidualized Bayesian Inference - Decision Tree (IBI-DT)\, that complement c onventional Genome-wide Association Studies (GWAS) in detecting genomic va riants of diseases for each individual. These tools improve the detection of genetic variants influencing complex diseases such as hypertension\, Pa rkinson's disease\, cancer\, and congenital heart disease (CHD) and facili tate the discovery of genetic interactions associated with these correspon ding complex diseases at the subgroup and individual level. By applying th e IBI method to hypertension\, we demonstrated its capability to identify unique and low-frequency variants influencing hypertension\, providing ins ights into personalized disease mechanisms that GWAS often misses. In Park inson’s disease research\, our approach not only pinpointed both establi shed and unknown risk factors but also developed predictive models that ut ilize these genetic markers to forecast disease risk effectively. For canc er\, the IBI-DT method identified key cancer drivers and their interaction s\, showing superior performance over traditional expression quantitative trait loci (eQTL) analysis. In the study of CHD\, IBI-DT proved more effec tive than GWAS by uncovering critical genetic influences\, revealing more novel and well-known genes\, gene interactions\, and essential biological pathways. This research integrates systems thinking with genomics to signi ficantly advance our understanding of diseases by identifying novel varian ts\, uncovering genetic network interactions\, and improving disease predi ction and comprehension. The dissertation represents systems engineering p rinciples\, offering scalable\, reproducible\, and efficient solutions for complex genomic data\, paving the way for future advancements in precisio n medicine. GEO:37.955324;-91.775108 LOCATION:Engineering Management Building\, 226 SUMMARY:Final Doctoral Defense for Md Asad Rahman URL;VALUE=URI:https://calendar.mst.edu/event/final-doctoral-defense-for-md- asad-rahman END:VEVENT END:VCALENDAR