Systems biomedicine is a relatively new field that focuses on the study of complex interactions in biological systems at a systemic level. Our goals are to study human diseases especially brain diseases from the systemic view, by combining various data sets. Our main research interests focus on Microarray Data Analysis, Network Biology and Imaging Genetics.

Microarray Data Analysis
Microarray Data Analysis mainly concentrates on developing novel algorithms for classification, clustering and disease feature gene selection from microarrays. We are also interested in discovering microRNA markers of brain diseases from microRNA microarray.

Network Biology
Network Biology includes applying machine learning, data mining and statistics methods to reconstruct and analyze various complex biological networks, incorporating interactome with diverse omics datasets such as transcriptomics and phenomics datasets, and further to find disease-related genes or gene sub-networks.

Imaging Genetics
The theme of Imaging Genomics in this team aims at the genetic basis of anatomical and functional abnormalities in various neurological and psychiatric diseases found by neuroimaging. Our studies are also dedicated to develop and apply novel pattern recognition and machine learning algorithms combining imaging information with genomics data from system-level perspectives to find the biomarker for complex brain disease (such as schizophrenia, Alzheimer's disease, and glioma etc.).