I am currently working on my Master’s research in Professor Manolis Kellis’ lab at MIT from September 2024 to June 2025. I am studying the genomic basis of opioid use disorder (OUD), an epidemic that kills over a hundred people every day.

My first goal is to identify the genes that are dysregulated in addiction through differential gene expression analysis. For this, I am using single-cell RNA-seq data from postmortem patient brain tissue from the Brain Endowment Bank at the University of Miami (sequenced by the Kellis Lab in-house). I pseudo-bulked the data by sample before applying differential gene expression analysis. I plan to complete these analyses for each cell type, brain region, sex, and age group to assess differences across cell populations and individuals. Some preliminary results are shown below, sorted in descending order of genes that are most differentially expressed within Inhibitory neurons (Inh).

My second goal is to model the gene regulatory network as a bipartite graph that links transcription factors to target genes using Perturb-seq data.

I am implementing these statistical and machine learning approaches in Python, and this research will form the basis of my Master’s thesis.