Biostatistics & Bioinformatics
The Biostatistics and Bioinformatics research group in the Department of Statistics at Penn State develops cutting-edge statistical and computational methods to address complex challenges across the life sciences, public health, and biomedical research. Our faculty and students work on problems spanning bioinformatics, molecular biology, epidemiology, global health, and precision medicine, with applications that range from understanding the spread of infectious diseases to analyzing large-scale genomic and population health data. We create novel statistical designs, computational tools, and data-integration strategies to analyze complex and high-dimensional data, ensuring that our methods drive impactful discoveries in population health, medicine and evolution.
Statistical methods have always been instrumental to the life sciences, public health, and biomedical research, and their importance has grown with the advent of high-throughput “omics” technologies, disease surveillance and surveys, electronic medical records, and advanced medical imaging. Leveraging expertise across diverse areas of statistics, our faculty lead research on genomic and multi-omics analysis, spatial and spatio-temporal modeling, population size estimation, causal inference in health studies, and machine learning for public health decision-making. Our work is supported by the National Institutes of Health, the National Science Foundation, the Huck Institutes for the Life Sciences, U.S. Centers for Disease Control and Prevention, World Health Organization, and Joint United Nations Programme on HIV/AIDS, and many faculty are active members of interdisciplinary centers such as the Center for Medical Genomics (CMG), the Center for Computational Biology and Bioinformatics (CCBB), and the Center for Infectious Disease Dynamics (CIDD). Through these collaborations, our team transforms data into actionable insights that inform health policies, guide clinical trials, and advance precision health initiatives.
Faculty
Faculty and Student Research Collaborations
Unusual DNA folding increases the rates of mutations
DNA sequences that can fold into shapes other than the classic double helix tend to have higher mutation rates than other regions in the human genome. New research shows that the elevated mutation rate in these sequences plays a major role in determining regional variation in mutation rates across the genome. Deciphering the patterns and causes of regional variation in mutation rates is important both for understanding evolution and for predicting sites of new mutations that could lead to disease.
“Most of the time we think about DNA as the classic double helix; this basic form is referred to as ‘B-DNA,’” said Wilfried Guiblet, co-first author of the paper, a graduate student at Penn State at the time of research and now a postdoctoral scholar at the National Cancer Institute. “But, as much as 13% of the human genome can fold into different conformations called ‘non-B DNA.’ We wanted to explore what role, if any, this non-B DNA played in variation that we see in mutation rates among different regions of the genome.”
A paper describing the research by a team of Penn State scientists is available online in the journal Nucleic Acids Research.