معرفی
Sunduz Keles is a Professor of Statistics and Biostatistics & Medical Informatics at the University of Wisconsin–Madison, affiliated with the School of Computer, Data & Information Sciences. Her research focuses on statistical genomics, computational biology, and biostatistical methods, with particular emphasis on epigenetic mechanisms, DNA methylation in neurodegenerative diseases, and integrative analysis of multi-omics data. She develops machine learning platforms for biological systems and applies statistical methods to understand genetic and cellular processes.
Her work spans computational methodologies for analyzing genomic data, including Hi-C studies, single-cell RNA sequencing, and ChIP-seq experiments. Recent projects include investigating sex-specific epigenetic changes in Alzheimer’s disease, regenerative potential of cytokines in heart repair, and GATA2-dependent signaling in hematopoiesis. Dr. Keles collaborates on translational research, such as clinical genetic variant curation systems and predictive modeling for disease pathogenesis.
Publications highlight advancements in statistical frameworks for genomics, including algorithms for gene-enhancer interaction inference and tensor modeling of 3D genome data. Her interdisciplinary approach bridges biostatistics, computer science, and molecular biology to address complex biological questions.
No scientific awards are explicitly mentioned in the provided materials. Her advising and grants are not detailed here, though her role as a professor implies active mentorship in statistical genomics and computational biology. She is associated with the Department of Statistics and affiliated research groups at UW–Madison.
