A Chemical Engineering's Approach to Systems Biology-Microfluidics, Automation and Big Data

Colloquium | January 22 | 4-6 p.m. | 180 Tan Hall

 Hang Lu, Professor, Georgia Institute of Technology

 Department of Chemical Engineering

My lab is interested in engineering micro systems and automation tools to address questions in systems neuroscience, developmental biology, and cell biology that are difficult to answer with conventional techniques. Micro technologies provide the appropriate length scale for investigating molecules, cells, and small organisms; moreover, one can also take advantage of unique phenomena associated with small-scale flow and field effects, as well as unprecedented parallelization and automation to gather quantitative and large-scale data about complex biological systems. I will show how continuous flow, multi-phase flow, and open microfluidic systems can be used to culture, manipulate, image, and stimulate samples. I will show how image informatics and statistical machine learning techniques can greatly enhance our ability to understand the information carried in images and video microscopy data. We apply these techniques to address a variety of questions in developmental and behavioral neurogenetics, and aging in a soil nematode C. elegans, which have implications in human developmental, psychiatric, and age-related neural disorders.

 pollyn@berkeley.edu, 510-643-3987