Advancing Biomarker and Mechanistic Discovery of Human Disease through Machine Learning
Speaker: Prof. Juan Cui
University of Nebraska-Lincoln (UNL)
DEIB - Alario Room (Bld. 21)
June 26th, 2024 | 2.30 pm
Contact: Prof. Maurizio Magarini
Research Line: Information transmission
University of Nebraska-Lincoln (UNL)
DEIB - Alario Room (Bld. 21)
June 26th, 2024 | 2.30 pm
Contact: Prof. Maurizio Magarini
Research Line: Information transmission
Sommario
On June 26th, 2024 at 2.30 pm the seminar "Advancing Biomarker and Mechanistic Discovery of Human Disease through Machine Learning" will take place at DEIB Alario Room (Building 21).
Rapid advances in machine learning and the accumulation of large-scale omics data have resulted in unprecedented opportunities and challenges for researchers studying complex human diseases systematically. In this talk, I will introduce our recent work in biomarker discovery and RNA-dependent cell-cell communication in human cancer diagnosis and mechanistic discovery, leveraging emerging techniques in genomics and machine learning.
Juan Cui, Ph.D., is an Associate Professor in the School of Computing at the University of Nebraska-Lincoln (UNL). She earned her Ph.D. in Computational Biology and Bioinformatics from the National University of Singapore and conducted her postdoctoral research in cancer informatics at the University of Georgia. Currently, she holds courtesy appointments in the School of Biological Sciences at UNL and the Department of Molecular Biology and Biochemistry at the University of Nebraska Medical Center. Dr. Cui has published over 80 scientific articles, co-authored a book on cancer bioinformatics, and contributed four book chapters in the fields of Bioinformatics and Computational Biology, Biomedical Data Analytics, and Cancer Research.
She also holds two U.S. patents for cancer diagnostic biomarker discovery. Active in the academic community, she serves on journal editorial boards and program committees of international conferences and workshops in bioinformatics. Her primary research interest at UNL is developing integrated computational solutions for human disease research. Her group’s work spans multi-omics and machine learning-enabled biomarker discovery, modeling cancer genome evolution, RNA regulation, cellular communication, diet and health linkage, and technologies for smart health management. Dr. Cui’s research focuses not only on developing cutting-edge technologies for clinical decision-making but also on making mechanistic discoveries of disease underpinnings to enhance our understanding. Her research has been funded by NIH and USDA/NIFA.
Rapid advances in machine learning and the accumulation of large-scale omics data have resulted in unprecedented opportunities and challenges for researchers studying complex human diseases systematically. In this talk, I will introduce our recent work in biomarker discovery and RNA-dependent cell-cell communication in human cancer diagnosis and mechanistic discovery, leveraging emerging techniques in genomics and machine learning.
Juan Cui, Ph.D., is an Associate Professor in the School of Computing at the University of Nebraska-Lincoln (UNL). She earned her Ph.D. in Computational Biology and Bioinformatics from the National University of Singapore and conducted her postdoctoral research in cancer informatics at the University of Georgia. Currently, she holds courtesy appointments in the School of Biological Sciences at UNL and the Department of Molecular Biology and Biochemistry at the University of Nebraska Medical Center. Dr. Cui has published over 80 scientific articles, co-authored a book on cancer bioinformatics, and contributed four book chapters in the fields of Bioinformatics and Computational Biology, Biomedical Data Analytics, and Cancer Research.
She also holds two U.S. patents for cancer diagnostic biomarker discovery. Active in the academic community, she serves on journal editorial boards and program committees of international conferences and workshops in bioinformatics. Her primary research interest at UNL is developing integrated computational solutions for human disease research. Her group’s work spans multi-omics and machine learning-enabled biomarker discovery, modeling cancer genome evolution, RNA regulation, cellular communication, diet and health linkage, and technologies for smart health management. Dr. Cui’s research focuses not only on developing cutting-edge technologies for clinical decision-making but also on making mechanistic discoveries of disease underpinnings to enhance our understanding. Her research has been funded by NIH and USDA/NIFA.
