Mihaela Pertea, PhD

Research Interests

Our group focuses on developing innovative and efficient methods to analyze large DNA and RNA sequence data sets in order to provide a genome-scale understanding of cellular function. Our research contributions integrate sophisticated machine learning techniques and statistical methods for identifying stretches of genomic DNA that have a biological function.This includes protein-coding genes, noncoding RNA genes, and regulatory regions that control the genes. A huge and still-growing number of genetic studies depend on accurate and complete gene descriptions, so our current research effort continues to be dedicated towards both the creation of computational pipelines that will improve the gene annotation as well as in maintaining the existing gene catalogues.

Titles

• Associate Professor, Biomedical Engineering
• Associate Professor, Genetic Medicine
• Affiliate Associate Professor, Computer Science

Affiliated Centers & Institutes

• Center for Computational Biology

Education

• PhD, Computer Science, Johns Hopkins University, 2001
• MSE, Computer Science, Johns Hopkins University, 1998
• MS, Computer Science, University of Bucharest, 1995
• BS, Psychology, University of Bucharest, 1995
• BS, Computer Science, University of Bucharest, 1994

Recent Highlights

December 16, 2019

Meet Mihaela Pertea, associate professor of BME

Mihaela Pertea joined the Johns Hopkins Department of Biomedical Engineering as an associate professor in July 2019. In this interview, she discusses her research in computational genomics, her career journey, and advice for students.