Advanced Analysis Platform for Nanotechnology Research

Abstract

This dissertation presents the design and development of an advanced, interactive analysis platform to support research in dynamic DNA nanotechnology. Modern DNA-based assays generate large, complex datasets that require efficient visualization, robust statistical processing, and reproducible reporting. However, existing tools often demand substantial programming knowledge, limiting accessibility for experimental scientists and slowing interdisciplinary collaboration.

To address these challenges, this project extends the Nanosuite framework with a Jupyter-based Interactive Assay Explorer that integrates data import, validation, visualization, statistical analysis, and automated report generation within a single environment. The system provides a human-centred interface that enables researchers to explore fluorescence time-series and endpoint assays, compare samples, examine reaction behaviours, and generate publication-ready reports in HTML, PDF, and CSV formats.

The platform was evaluated using seven real assay datasets representing diverse experimental conditions. The results demonstrate that the system reliably processes high-volume data, identifies configuration inconsistencies, supports interactive exploration, and produces reproducible analytical outputs. By reducing technical barriers and enhancing clarity, automation, and reproducibility, this work offers a practical and scalable solution that strengthens analytical workflows in dynamic DNA nanotechnology research