The brain is the most complex organ in the body, composed of different types of cells connected by intricate networks essential for sensory perception, cognition, and behavior. Understanding how these cells are organized, connected, and functionally coordinated within the brain remains a significant scientific challenge. Recent technological advances have produced large amounts of structural and functional data of the brain, yet extracting meaningful biological insights from these complex datasets remains difficult. This research addresses this critical gap by creating computational tools integrating molecular data with structural imaging, offering a detailed view of brain organization. Specifically, the project leverages datasets from advanced imaging methods revealing fine anatomical details with spatial transcriptomics, a technique profiling gene expression within tissues. By integrating these complementary data types using novel Bayesian and deep learning modeling frameworks, the project aims to build the first comprehensive 3-dimensional molecular and structural map of brain areas for olfaction in mice, an important model system for understanding neural circuits. This map will provide fundamental insights into how molecular characteristics of neurons relate to their structural connections, enhancing our understanding of how brain circuits’ function. Broader impacts include training a new generation of interdisciplinary scientists skilled in the intersection of artificial