BME MS Thesis Defense: Electra Scarpignato

Title: "ENHANCING THE ACCESSIBILITY OF HIGH-DIMENSIONAL DATA ANALYSIS: A CASE STUDY ON THE PANDORA PLATFORM"

Advisory Committee: Chair - Dr. Brian DePasquale, BU BME Member 2: Dr. Diane Joseph-McCarthy, BU BME Member 3: Dr. Adriana Tomic, BU BME

Abstract: The generation of high-dimensional omics data in biomedical research presents significant challenges in analysis, visualization, and interpretation of output. While existing platforms feature advanced statistical analysis and machine learning methods, they are often complex and difficult for researchers lacking computational expertise to utilize. The PANDORA software developed by Atomic Lab seeks to improve accessibility of these advanced tools while supporting predictive modeling and biomarker discovery by leveraging advanced statistical methods for high-dimensional data analysis. However, the complexity of the software’s underlying tools and algorithms hinders accessibility and widespread adoption among biomedical researchers. This thesis addresses this issue by undertaking a comprehensive, user-centric redesign of the PANDORA platform’s documentation to transform existing technical guides into an intuitive and highly accessible resource that empowers biomedical researchers to confidently perform end-to-end analysis of their data. This work provides a framework for improving documentation of specialized scientific software, thereby contributing to more efficient and reproducible research outcomes.