UCLA Center for Neurobehavioral Genetics

2020.6 - 2022.6

This is actually the first research lab I joined in my undergraduate. Genuine thanks to Prof Roel Ophoff and Toni Boltz :)

I mainly perform basic data processing and analysis tasks. I processed RNA sequence data and performed various data analysis and visualization methods on them using Python and R.

I co-authored two papers during my research at the lab

“Powerful eQTL mapping through low-coverage RNA sequencing”. We showed that Low-coverage RNA sequencing is an effective approach in Expression quantitative trait loci studies and can save the cost by more than 50%.
“Cell type deconvolution of bulk blood RNA-Seq to reveal biological insights of neuropsychiatric disorders”. We employ computational methods to deconvolute bulk RNA-Seq data from 1,730 blood samples, highlighting cell-specific genetic associations with bipolar disorder and schizophrenia. By inferring cell type proportions and expressions, our approach offers a refined lens to discern previously masked trait-relevant mechanisms, underscoring the transformative potential of computational strategies in neuropsychiatric research.

Back in college, I dipped my toes into bioinformatics research for the first time. Those days were packed with awesome memories, loads of learning, and hands-on research experience. It felt amazing to see the stuff I’d learned come to life in something so meaningful.

After graduation I decided to step away from the bioinformatics lab since I thought that I need to focus more on my major stuff. So instead, I dived head-first into cool tech areas like reinforcement learning, computer vision, and multi-modal learning. But here’s the twist: the deeper I got into these fields, the more I realized they have crazy potential in biology and medicine.

So, here I am, thinking about how to merge these worlds together. I’m now looking into AI for Medicine/Bio Ph.D. programs, eager to bring all this tech goodness back to the world of medicine and biology. Exciting times ahead!