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Robust Algorithms For Detecting Hidden Structure In Biological Data, Roman Sloutsky
Robust Algorithms For Detecting Hidden Structure In Biological Data, Roman Sloutsky
Arts & Sciences Electronic Theses and Dissertations
Biological data, such as molecular abundance measurements and protein
sequences, harbor complex hidden structure that reflects its underlying
biological mechanisms. For example, high-throughput abundance measurements
provide a snapshot the global state of a living cell, while homologous
protein sequences encode the residue-level logic of the proteins' function
and provide a snapshot of the evolutionary trajectory of the protein family.
In this work I describe algorithmic approaches and analysis software I
developed for uncovering hidden structure in both kinds of data.
Clustering is an unsurpervised machine learning technique commonly used
to map the structure of data collected in high-throughput experiments,
such …