Comparative Topological Analysis of Neuronal Arbors via Sequence Representation and Alignment
Date
2015
Authors
Gillette, Todd Aaron
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Abstract
Neuronal 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.
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Keywords
Nanoscience, Bioinformatics, Motif analysis, Neuroinformatics, Neuronal morphology, Neuronal reconstruction, Sequence alignment