|Undergraduate Institution:||University of Maryland - Baltimore County|
|Department:||Bioinformatics & Computational Biology|
Breast cancer is a heterogeneous disease that varies in histological forms, clinical outcomes, genomic and genetic alterations, and molecular classifications. We hypothesize that the variability are in part caused by specific genetic and genomic DNA copy number alterations (CNA). Given the large number of CNAs that exist in human breast cancers, finding the most frequent and important ones is key to advancing therapeutics because it is likely that these recurrent CNAs are breast tumor drivers. My research focuses on developing a statistical and computational framework, including methods and software, for CNA analysis and related studies to identify recurrent CNAs, and the driving genes from these CNAs.