Thesis Advisor:
Prof. Hang Lu (School of Chemical and Biomolecular Engineering, Georgia Tech)

Committee Members:
Prof. Mark Styczynski (School of Chemical and Biomolecular Engineering, Georgia Tech)
Prof. Patrick McGrath (School of Biological Sciences, Georgia Tech)
Prof. Todd Sulchek (School of Mechanical Engineering, Georgia Tech)
Prof. Eva Dyer (School of Biomedical Engineering, Georgia Tech)

Automated pipeline for building whole-brain anatomical atlases and comparative analysis of diverse biological factors in C. elegans

Abstract
The roundworm C. elegans offers a unique opportunity as a model organism to develop necessary methodologies for studying head anatomy. Existing approaches, while providing valuable insights, have technical limitations in terms of accuracy, throughput, robustness, and accessibility. This proposal introduces an optimized pipeline to overcome these challenges and explore its application across diverse scenarios. In aim 1, an experimental and computational pipeline will be presented for constructing complete whole-brain data-driven anatomical atlases for N2 young adult worms. In Aim 2, the pipeline will be adapted for comparative studies across various biological factors such as genetic backgrounds and developmental stages, with carefully chosen metrics to understand underlying biology from observed differences. In Aim 3, our standard N2 atlas will be incorporated to address challenges in functional imaging analysis, accompanied by advancements in image processing techniques. This proposed pipeline has the potential to enhance our understanding of C. elegans brain and may contribute to a broader comprehension of nervous systems in other biological organisms.