By Shannon Turgeon
Photography by Joshua Franzos
Hatice Ülkü Osmanbeyoğlu began exploring biomedical informatics—a rapidly evolving area of study that involves using technology to improve medical research and clinical care—at the University of Pittsburgh as a doctoral student.
Osmanbeyoğlu, who is now an associate professor of biomedical informatics at Pitt’s School of Medicine, quickly took an interest in complex omics data—vast molecular readouts that reveal how cells and systems function. That curiosity soon evolved into a career developing computational tools that turn this data into biological and therapeutic insights.
On Friday, Nov. 14, Osmanbeyoğlu will present “Unraveling Disease Insights Through Machine Learning and Multiomics” as part of the 2025 Senior Vice Chancellor’s Research Seminar Series. (Join the lecture here.)
Osmanbeyoğlu’s research works to decode tissue microenvironments for disease research using omics and computational modeling. She is particularly interested in modeling transcriptional regulation, and studies transcription factors in both normal and disease contexts.
Her group uses bulk, single-cell, and spatial multiomics data—including genomics, epigenomics, transcriptomics, and proteomics—to model how transcription factors orchestrate cellular states. This approach allows her team to infer transcription factor activity and uncover regulatory mechanisms that drive disease.
At the beginning of her career, Osmanbeyoğlu focused on studying cancer, which occurs when there are disruptions in the pathways and transcription factors that control how our cells operate.
She is now expanding the scope of her research by working with Pitt’s Center for Transcriptional Medicine (CTM). CTM is working towards developing RNA-based transcriptional therapeutics to treat end-stage organ diseases—a process that involves rewriting the codes of the transcription networks that Osmanbeyoğlu studies.
Her research team is now using data extracted from the tissues and cells of diseased organs to identify the transcription factors that are disrupted during end-stage diseases, such as chronic kidney, lung, and neurodegenerative diseases.
“This was a turning point in my research to make it more translational. By collaborating with different disciplines, we can make more of an impact,” she said.
In addition, her team recently applied its tools to publicly available data on glioblastoma tumors and created a web resource application where researchers can search for information by tumor transcription factor and pathway activity, receptor expression and more. She is also developing methods to predict key protein markers from spatial gene maps, providing a clearer view of cellular function and organization.
By making these tools widely accessible, Osmanbeyoğlu is helping scientists turn complex data into meaningful discovery.
“As informaticians, we can use this data and answer different questions. So that is what I'm trying to do: integrate publicly available data, apply our tools and create a resource for the community,” said Osmanbeyoğlu.
Osmanbeyoğlu believes that as modern technology develops and more data becomes available, the research and collaboration occurring in her field—and at Pitt specifically— will lead to more timely discoveries that will have a long-term impact on medicine.
“I want to work on diseases where we don't currently have cures, and Pitt is a nice environment for this, with cutting-edge research in so many different areas,” she said.