Mining Electronic Health Records for Discovery
Dr. Sarah Pendergrass (Geisinger Health System)
Wondering about what you want to pursue after graduate school? While it is common for people to reach for post doctoral positions, maybe you’ve also considered careers outside of academia. There are many career paths you could follow, including industry and research scientist positions. Our HGSAC invited speaker will be discussing her career path that led her to become an investigator at Geisinger Health System, and will describe her work as a genetic bioinformatician. Open dialogue is encouraged.
Dr. Sarah Pendergrass is an Investigator I in the Biomedical and Translational Informatics Program at Geisinger Health System. Her work focuses on high-throughput data analysis and data-mining projects for uncovering the genetic architecture of complex human diseases and traits. This includes coupling genotypic data with de-identified electronic health record data, population survey based data, clinical study data, and pharmacological study data. She is interested in incorporating environmental exposure data in analyses of disease susceptibility, and analyses across ancestry. She has extensive experience developing novel methodologies and performing high-throughput analyses for discovery, such as those for Phenome-Wide Association Studies (PheWAS), which work to identify cross-phenotype associations and pleiotropy.
During her PhD at Dartmouth College, she worked on gene-expression analyses and bioinformatics, with projects leveraging the complexity of gene-expression data for biomarker and biological discovery for the disease Systemic Sclerosis. She is a former staff scientist of Dr. Marylyn Ricthie where she did GWAS studies and computational biology. Her masters work in Biomedical Engineering, and undergraduate degree in Physics, have provided her with additional technical and analytical expertise for complex data-driven projects.
Sarah also has extensive experience with developing software tools aimed at analyzing and visualizing complex data including PhenoGram, PhenoGram-Genie, Synthesis-View, and PheWAS-View.
This event is hosted by the Huck Graduate Student Advisory Committee (HGSAC) and the BMB department as part of the Career & Professional Development Seminar Series.