ECE Departmental Seminar
Systematic Multi-scale Modeling and Analysis for Gene Regulation
Department of Biomedical Informatics
Stony Brook University
Friday, 12/2/16, 1:00pm
Light Engineering 250
Abstract: The rapidly increasing quantity of biological data offers novel and diverse resources to study biological functions at the system level. Integrating and mining these various large-scale datasets is both a central priority and a great challenge for the field of systems biology and necessitates the development of specialized computational approaches. In this talk, I will present several novel computational systems approaches in a multi-scale modeling framework to study gene expression and regulation with applications to cancer and developmental biology: 1) an algorithm to simultaneously cluster multi-layer networks such as gene co-expression networks across multiple species, which discovered novel human developmental genomic functions and behaviors; 2) a logic-circuit based method to identify the genome-wide cooperative logics among gene regulatory factors and pathways for the first time in cancers such as acute myeloid leukemia, which provided unprecedented insights into the gene regulatory logics in complex biological systems; 3) an integrated method using the state-space model and dimensionality reduction to identify principal temporal expression patterns driven by internal and external gene regulatory networks, which established an entirely new analytical platform to identify systematic and robust dynamic patterns from high dimensional, complex and noisy biomedical data. In addition, I will introduce some ongoing research projects and discuss the future directions where multi-scale approaches can make a significant impact in systems biology.
Bio: Dr. Daifeng Wang is a tenure-track Assistant Professor in the Department of Biomedical Informatics at Stony Brook University, and a faculty member of Stony Brook Cancer Center. He received his Bachelor’s degree in Electronics and Information Engineering from Huazhong University of Science and Technology, Wuhan, China in 2004, and his Ph.D. degree in Electrical and Computer Engineering from the University of Texas at Austin in 2011. He joined Gerstein Lab as postdoctoral associate in 2012 and associate research scientist in 2015 in Yale University. His research has focused on bioinformatics, computational systems biology and biomedical informatics. He published his recent work in Nature, Genome Biology, PLoS Computational Biology, PNAS, IEEE/ACM Transactions on Computational Biology and Bioinformatics, PLoS ONE.