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
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
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June 25, 2025A new software tool can transfer annotations between the genomes of different species to map out new genomes far more quickly than current methods.
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April 1, 2025Mihaela Pertea and Sri Sarma honored for outstanding contributions to engineering and medicine research, practice, or education.
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December 11, 2024A recent innovation from Johns Hopkins researchers enables deeper insights into gene function and disease-linked mutations.