Interpreting Design Principles of Human Cells from Big Data

Date(s) - 11/12/2015
4:00 pm

Amina Ann Qutub, Ph.D., Assistant Professor, Department of Bioengineering, Rice University

Interpreting Design Principles of Human Cells from Big Data

My research vision is to harness the natural behavior of human cells in order to understand and improve health. One natural behavior critical to life – how our body responds to oxygen – and lack thereof – drives the progression of many diseases: e.g., ischemic stroke, Alzheimer’s, and leukemia. My lab is developing new methods in multiscale modeling, interactive visualization, and machine learning, and applying them to live cell imaging and patient biopsy data to tackle the challenge of interpreting how changes in hypoxic response at the molecular level affect cell dynamics. Two questions underlie this work: (1) How are the states of molecular networks correlated to cell structures and behaviors? (2) How do single cells communicate to form complex tissues? We are using knowledge gained in answering these two questions to impact clinical decision making and drug development. I will show how we are using our methods to study cells of the neurovasculature and in cancer cells, with applications to aiding the design of neuroregenerative strategies and chemotherapies.

Brief Bio:

Amina received her PhD in Bioengineering from the University of California, Berkeley and UCSF, and a B.S. in Chemical Engineering from Rice University. Following her postdoctoral training in Biomedical Engineering at Johns Hopkins University, School of Medicine, she joined Rice University where she is an Assistant Professor in the Department of Bioengineering.

Her research interests are in neurovascular systems biology, cell engineering, and hypoxic response. Her lab’s research vision is to harness human cells’ natural behavior in order to understand and improve health. Specifically, Amina develops tightly coupled experimental-computational methods to identify the natural behaviors of brain cells (e.g., differentiation) and characterize the aberrant behaviors of cancer cells, and how they are constrained by molecular signaling as cells develop into functional tissue. She has authored or coauthored 30 publications; cofounded the tech startup DiBS; and served as scientific lead of a 2014-2015 DREAM Biomedical Big Data Algorithm Challenge, after winning a 2013 DREAM subchallenge for interactive data visualizations. Amina is a NSF CAREER and NSF Neural & Cognitive Systems awardee. Her research is currently supported by NSF, NIH, the Cancer Prevention Research Institute of Texas, and the Hamill Foundation.