I am fifth-year Ph.D. student from Department of Statistics in the University of Wisconsin - Madison and I have been developing statistical methods and computation tools to address challenges arisen from biological, and biomedical sciences under the supervision of Dr. Sündüz Keleş since 2014.
My dissertation research focuses on: 1. Developing novel methods and software that integrate multi-omics data with Hi-C and other “C”-related data to elucidate mechanisms of long-range interactions and their roles in gene regulation; 2. Investigating the impact of repetitive regions of the genomes on chromatin structure formation and pursue their contribution to development and disease.
I also built a repertoire of collaborative research experience with both statisticians and computational biologists inside and outside of campus, and principal investigators, from the Blood Research Program at UW-Madison. I have co-led one and participated in two projects to study the GATA-1/Heme regulation mechanism leveraging ChIP-seq, ATAC-seq, and RNA-seq data. Looking forward to applying my statistical and computational expertise to novel and intriguing problems in other disciplines and initiate collaboration.
Ph.D. Candidate in Statistcs - Minor in Quantitative Biology , 2014 - 2019 (Expected)
University of Wisconsin - Madison
B.E. in Statistics, 2010 - 2014
Renmin University of China
Collaborative Work with the Bresnick Lab:
Utilization of Hi-C multi-mapping reads; Fast simulation of Hi-C interactions; Hi-C differential interactions detection.
mHiC: Python pipeline of multi-mapping strategy for Hi-C data by probabilistically assigning reads originatedfrom repetitive regions. Major computing parts are accelerated by C.
FreeHiC: Python pipeline using FRagment Interactions Empirical Estimation method for fast simulation of Hi-C and other 3D proximity ligation sequencing data. Major computing parts are accelerated by C.
TreeHiC: R package for constructing hierarchical tree-structured multiple testing procedure for detecting differential chromatin interactions across different conditions. (Co-developer)
permseq: R package for mapping protein-DNA interactions in highly repetitive regions of the genomes with prior-enhanced read mapping.
permseqExample: R package for the permseq package illustration and demo runs. Smaller raw data and demo R scripts are provided for quick runs in order to get to know permseq package.