Bioinformatics

Biomedical research generates more sequencing data than ever before, leading to data analysis frequently becoming a bottleneck. I strive to develop data processing pipelines that can rapidly and accurately identify cellular features relevant to the chosen research question.

Hi-C Sequencing

Distant DNA interactions have emerged as an important layer of regulation. In our 2019 Genome Research paper, we apply Hi-C to study the 3D genome of adult glioblastoma, identifying numerous changes in fine-scale DNA loops and broad-scale compartmentalization between tumors.

RNA-seq (bulk and single-cell)

Differential transcription between cell populations or conditions can pinpoint the genes or pathways responsible for distinct cellular behavior. My research has applied RNA-Seq in diverse situations ranging from single-cell analysis of human brain tumors to hypoxia and stem cell regulation in Drosophila.

ChIP-Seq

Proteins bound to DNA can have many downstream effects on DNA replication, repair, and transcription. I have applied ChIP-Seq to identify narrow peaks associated with transcription factor binding and broad peaks associated with post-translational modifications of histones. ChIP-seq features prominently in our 2019 Genome Research paper as well as other forthcoming work.