The Monaghan Laboratory is actively involved on the forefront of regeneration biology research, and ongoing projects are investigating gene expression dynamics involved in regeneration biology in the axolotl. It is known that limb regeneration in the axolotl is highly similar to early development at the transcriptional level. In addition, specific mitogen gradients, retained cellular identity, expression factors, and cell-type specific markers have been previously shown as essential to both developmental and regenerative processes. However, an inability to visualize these dynamics 3-dimensionally in situ has remained unaddressed, limiting the ability to hypothesize on complex patterning mechanisms and localized expression. The Monaghan Laboratory has been successfully utilizing novel V3 HCR-FISH technique to produce spatial profiles of gene expression in the regenerating axolotl limb in situ in ongoing projects, and my project is focused on the image analysis and computational biology portion of the profiling pipeline. I have studied and developed a variety of functional protocols and programming frameworks that can be used to process raw data from fluorescent microscopy and extract quantifiable datasets. Through the use of such softwares as FIJI, ICY, and QuPath; programming languages such as Python; and contextualized machine learning platforms like Ilastik, I have created workflows that meet the imaging and data analysis needs of ongoing projects in the Monaghan Laboratory. These automated protocols have been optimized to process large quantities of data sequentially in an efficient, accurate, and reproducible manner.