As a jack-of-all-trades bioinformatician, I started in the biotechnology industry and slowly transitioned to academic biomedical research. I have a broad spectrum of experience through various roles in the biotechnology and healthcare industry, coupled with an even wider interest in all things intersection of biology and technology.
As a Research Bioinformatician at Cedars-Sinai, I oversee bioinformatics analyses supporting research in transplant translational immunology and reproductive medicine, including RNA sequencing, spatial transcriptomics, and other multi-omics approaches. Previously, my research focused on gene regulation in epithelial ovarian cancer and endometriosis. I have extensive experience collaborating with bench scientists, graduate students, postdoctoral researchers, clinical investigators, physicians, and bioinformaticians across multi-omics, translational, and epidemiological research projects.
I am skilled in scientific programming (bash, python, SQL, and R) and bioinformatics (pipeline development and data analysis for NGS-based omics) with working knowledge in HPC and cloud computing. I have led pilot studies for applying new NGS assays in ovarian cancer research, developed and documented best programming and data visualization practices, and mentored undergraduate interns in their bioinformatics projects. I also wrangled clinical/survey data and conducted statistical analysis. I am passionate about finding innovative solutions to complex biological problems and advancing the field of precision medicine.
My Selected Projects
- Tutorial/Presentation
- Pak’s Lawrenson Comp Bio Cookbook, Recipes for common data visualization used in genomics analysis and general EDA at Lawrenson Lab
- Exploring Spatial Omics and Beyond: A Bioinformatics Perspective, Invited talk given at Cedars Sinai Comprehensive Transplant Center (2024)
- Computational biology journal club presentation
- Intro to R Programming, Two-part R programming tutorial
- RNA-Seq: Pipeline and Analysis, A gentle introduction to rna-seq pipeline and analysis for wet-lab biologists
- CellChat, Two-part presentation on cell-cell communication analysis in scRNA-seq, including netSmooth, a network smoothing scRNA-seq imputation method
- Peak Calling Algorithm Overview, Overview of peak calling algorithms used in ChIP-seq
- Analysis/Tool
- Pipeline
- Cut and Tag Pipeline - Under Development
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Fun and miscellaneous
- Comparison of predicted SOX17 protein structure with dimethylated R150 between AlphaFold 2 + Vienna-PTM and AlphaFold 3 visualized in pymol

