Geneticist Marylyn Ritchie New Director for Penn’s Center for Translational Bioinformatics

caption: Marylyn RitchieMarylyn D. Ritchie, a nationally regarded geneticist and expert in using big data and machine-learning methods to improve human health, has been appointed as director, Center for Translational Bioinformatics, Institute for Biomedical Informatics (IBI) in the Perelman School of Medicine at Penn. Ritchie is also IBI’s associate director for bioinformatics and associate director of the Center for Precision Medicine.

“The recruitment of Dr. Ritchie represents a huge leap forward in Penn’s plan to be a leader in genomic and precision medicine,” said Daniel Rader, chair of the genetics department. “Dr. Ritchie will help leverage the Penn Medicine Biobank—among the largest in the country—and other genomic and phenomic resources at Penn Medicine into new discoveries and approaches to personalizing medical care.”

Dr. Ritchie has an accomplished record of research aimed at developing and applying computational and statistical tools and approaches to improve understanding of the fundamental genetic architecture of such diseases as cancer, diabetes, hypertension, chronic obstructive pulmonary disorder and cardiovascular disorders. Her expertise includes creating algorithms for detecting interactions between genes and between genes and the environment. The aim is to analyze the data associated with such interactions to understand how they might increase susceptibility to disease. These results can then be used to tailor treatments and predict future patient outcomes. She also specializes in systems genomics approaches. 

Before coming to Penn, Dr. Ritchie was the Paul Berg Professor of Biochemistry and Molecular Biology at Penn State University. She was also a professor in the Biomedical and Translational Informatics Institute and chief research informatics officer, both at Geisinger Health System.

Among her previous projects was leading a project at Geisinger Health System to link the genome data of over 50,000 patients with their medical histories, aiming to identify genetic and environmental sources of various diseases.