Ascoli, Giorgio A.Gillette, Todd Aaron2015-07-292015-07-292015https://hdl.handle.net/1920/9628Neuronal morphology is a key mediator of neuronal function, defining the profile of connectivity and shaping signal integration and propagation. Reconstructing neurite processes is technically challenging and thus data has historically been relatively sparse. Data collection and curation along with more efficient and reliable data production methods provide opportunities for the application of informatics to find new relationships and more effectively explore the field. This dissertation presents a method for aiding the development of data production as well as a novel representation and set of analyses for extracting morphological patterns.274 pagesenCopyright 2015 Todd Aaron GilletteNanoscienceBioinformaticsMotif analysisNeuroinformaticsNeuronal morphologyNeuronal reconstructionSequence alignmentComparative Topological Analysis of Neuronal Arbors via Sequence Representation and AlignmentDissertation