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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 …