Research
Bioinformatics and Computational Biology
Genomic Overload - Bioinformatics connects the dots
We apply systems biology approaches to integrate high-dimensional data sets, including static and dynamic imaging data, protein interactions, genetic interactions, biochemical pathways, and next-generation sequencing data on genomic sequence, RNA expression, DNA methylation, and chromatin modifications. Our goal is to obtain a quantitative understanding of complex biological systems. Current biological topics include:
Meiosis
A unique characteristic of germ cells is their ability to undergo meiosis, the process by which haploid gametes are produced. Errors in germ cells can lead to human infertility, miscarriages, birth defects, and cancers. We develop temporal-spatial dynamic models and statistical methods to investigate molecular and cellular mechanisms that regulate germ cell development.
Chromosome abnormality
Whole chromosome gains or losses are called aneuploidies. Changes in parts of chromosomes are referred to as segmental aneuploidies. Both lead to severe human developmental abnormalities even death through dosage effect and/or genome instability. We characterize the genome-scale impact of aneuploidies on gene expression and epigenetic changes.
Epigenome
Epigenetics is the study of heritable changes in gene expression and activity that are independent of the DNA sequence. Epigenetic mechanisms mediate biological responses to endogenous and exogenous stimuli that, when dysregulated, result in human diseases. We perform global analyses of epigenetic changes across the entire genome, including small RNA, DNA methylation, and histone modifications, to understand the host control of transposable elements.