About My Project

Understanding complexity, dynamics, and stochastic patterns in genomic data - concepts native to physics and mathematics - is critical for elucidating how disease states originate and evolve. In this project, we focus on the application of the Tunable Biclustering Algorithm (TuBA) to examine genetic and clinical data of cancer patients, aiming to identify genetic markers that can provide us insight into how cancers evolve. Our ultimate goal is to develop novel statistical platforms for fast translation of genomic data into clinical practice.

Week 1

On the first day of the REU, I attended the orientation and met with some other participants over zoom. Then, I spent the first half of the week familiarizing myself with the Tunable Biclustering Algorithm (TuBA), which is what I will implement over the summer.

During the second half of the week, I prepared for the presentation that will introduce my project. I gained more understanding about the direction I will take for the project this summer. I also downloaded the copy number and probe map data, and I wrote a function that combines these data with the bicluster information. This function allows me to combine bicluster information for any cancer with the copy number and probe map data, making future explorations more convenient. I started exploring some biclusters by creating visualizations in R.