People

I am interested in the areas of statistical genetics and epigenetics. Currently I am working on both developing novel methodologies and applying these methods to address real-world problems. My recent projects focus on methylation quantitative trait loci and substance-use disorders.

Dr. Xinyu Zhang is a computational biologist with experience of both scientific and industrial research.He has interdisciplinary knowledge and professional background in cross-fields: biology, oncology, biostatistics, and computer sciences. He was extensively experienced in bioinformatics platform/pipeline/algorithm development and construction, deep data analysis of NGS (Next Generation Sequencing) and microarray/chip, biomarker screening, longitudinal (or case/control) GWAS, EWAS, mQTL, eQTL, transcriptome, network (gene modules), system biology, translational bioinformatics. With strong algorithm development and excellent programming skills in Perl, R, Bash, C, PHP, SQL, Python, his The research interests focus on: 1) Autism early diagnosis genetic biomarkers (GWAS/CNV datasets); 2) Alcohol/cocaine addiction and its relation with HIV infection (EWAS/GWAS dataset); 3) Gene-Environmental interaction (methylation and Trauma) and its correlation with BMI (EWAS/Expression dataset). He works on computational medicine field as Associate Research Scientist in Yale Medical School since 2015. Papers and citations: http://scholar.google.com/citations?hl=en&user=9fiAMxAAAAAJ

I am interested in developing statistical methodologies to address scientific problems in medicine and public health, providing insights for more effective disease monitoring, prevention, and treatment. I am particularly drawn to the applications to human genetics and complex diseases. My recent projects focus on identifying the underlying genetic architecture of psychiatric disorders.  Papers and citations: https://scholar.google.com/citations?user=JTNog-QAAAAJ&hl=en

Xiaoyu Liang received her Ph.D from Michigan Technological University in 2018. Her research focuses on developing statistical methods and computational tools to map complex disease genes based on population data and pedigree data. Currently she is working on epigenome-wide association studies for alcohol consumption and developing an R package for simulating data from images to evaluate the performance of clustering algorithms.