Justin Cha

Justin Cha is a PhD student in the Computational Biology Program. He received his bachelor's degree in Biomedical Engineering at the Georgia Institute of Technology before working as an Associate Computational Biologist in the Getz Lab at the Broad Institute. For the Pugh lab, he works on software development and high-throughput computing (HTC) for the analysis of sequencing data.

# Research Interests

I have a general interest in genomics bioinformatics and software development, and I am currently working on a tool to identify and categorize DNA-protein binding sites based on occupancy patterns.


September 2018 – July 2021
Broad Institute of Harvard and MIT – Cambridge, MA

Associate Computational Biologist II

At the Broad Institute, I am a member of the Getz Lab, one of the world’s leading labs for cancer genomics. I have worked on several exciting projects pushing at the forefront of the field. One was an analysis of genomic progression in head and neck squamous cell carcinoma (HNSCC). For this project, I made use of a novel set of computational methods to reconstruct the trajectory of genomic events from exome sequencing data. This allowed us to see which mutations and other variants tend to occur early on in the progression of cancer, which will be useful in treatment development and prognosis.

August 2016 – May 2018
Integrative Systems Biology Lab – Atlanta, GA

Undergraduate Researcher

In the Integrative Systems Biology Lab at Georgia Tech, I worked with Dr. Denis Tsygankov on a project to simulate the biomechanics of solid tumors. For this project, I developed a tool to simulate densely packed cell populations under high pressure using time-evolving Voronoi diagrams, which is useful for analyzing tumor growth under specified conditions.

January 2017 – May 2017
Georgia Institute of Technology – Atlanta, GA

Data Analyst

As a data analyst for the Biomedical Engineering department of Georgia Tech, I worked with Professor James Rains to analyze the market data for hospitals in the United States. I created a UI using Matlab to easily analyze subsets of the data and used trends to identify market hotspots for medical devices.


"Genetic events associated with venetoclax resistance in CLL identified by whole exome sequencing of patient samples."

Blood, 2023

"Establishing the early genetic progression in cancers with unobtainable premalignant disease."

Nature Cancer, 2023

"Genomic profiling of smoldering multiple myeloma identifies patients at a high risk of disease progression.”

Journal of Clinical Oncology, 2020, 38(21), 2380-2389


“Tamoxifen instigates uterine cancer development by activating PI3K signaling and supersedes PIK3CA driver mutations.”

Cancer Research, 2022, 82(4_Supplement), pp.GS2-09-GS2-09.

“Mechanisms of primary and acquired resistance to venetoclax in chronic lymphocytic leukemia (CLL).”

Cancer Research, 2021, 81(13_Supplement), 1097-1097.


“Mechanisms of Primary and Acquired Resistance to Venetoclax in Chronic Lymphocytic Leukemia (CLL),”

American Association for Cancer Research, 2020

“Genomic landscape of metastatic breast cancer (MBC): comprehensive cell-free DNA analysis from over 10,000 patients and comparison with primary breast cancer,”

San Antonio Breast Cancer Symposium, 2020


Programming Languages
  • python
  • JavaScript
  • Matlab
  • SQL
  • Julia

  • Quantitative
  • Data analysis
  • Statistics
  • Genomics

  • Communication
  • Technical presentation/writing
  • Data visualization
  • Teaching
  • Tutorials