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Same school, new name. The School of Informatics and Computing is changing its name effective January 11, 2023. Learn more about the name change

Yunlong Liu, Ph.D.

  • Professor of Medical and Molecular Genetics, Biostatistics, and BioHealth Informatics
  • T. K. Li Chair for Medical Research
  • Co-director, Institute for Quantitative Biomedical Sciences (IQBS); Director, Center for Computational Biology and Bioinformatics (CCBB); Director, Center for Medical Genomics (CMG) Indiana University School of Medicine

Contact

yunliuiupui [dot] edu

Education

  • 1992-1996: B.Eng. in Control theories, Harbin Engineering University, Harbin, China
  • 1996-1999: M.Eng. in Control theories, Tsinghua University, Beijing, China
  • 2001-2004: Ph.D. in Biomedical Engineering, Purdue University, West Lafayette
  • 2004-2006: Postdoctoral fellow in Biochemistry, Indiana University School of Medicine

Biography

Dr. Yunlong Liu received his Ph.D. degree from Department of Biomedical Engineering at Purdue University in 2004, and then conducted postdoctoral training at the Edenberg Lab in the Department of Biochemistry at Indiana University School of Medicine.

Currently, he is an associate editor of BMC Genomics and serves on the editorial boards of several international bioinformatics journals. His research interests span over genomics, bioinformatics, and systems biology, with particular emphasis on biomedical applications. He is the recipient of Achievement Award for the 2007 World Congress in Computer Science, Computer Engineering & Applied Computing, and CAMDA (Critical Assessment of Missive Data Analysis) 2009 Best Presentation Award. His current research is fully supported by NIH with multiple active grants from NIA, and NIAAA and NCRR.

Research Interests

The Liu Laboratory (Laboratory for Computational Genomics) uses systems biology approaches to understand regulatory mechanisms of gene expression, including transcriptional regulation, post-transcriptional regulation, and epigenetic regulation. This area involves several interdisciplinary components, including functional genomics, genetics, computational and statistical modeling, computer science/engineering, and data management.