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PhD Final Oral Examination – Ben Tribelhorn


Friday, June 14, 2013 10:00 AM - 12:00 PM

Computational Methods for Protein-Protein Interface Prediction
Protein-protein interactions underlie all biological processes and are a field of study that has wide implications throughout many other fields including medicine, genetics, biology, and ecology. Proteins are the building blocks and primary actors of life. They work together to accomplish virtually every task within a cell, including, metabolism, signal propagation, immune responses, and cell signaling. This problem is a logical successor to the Human Genome Project: now that we know so much about the DNA of living organisms, how do we advance our knowledge? The Human Genome and other DNA sequencing efforts have provided complete genetic sequences for more than 180 living organisms. However, these efforts fall short of describing or predicting life processes because the sequence of a protein is not enough to elucidate its function. Knowing this, the National Institute of Health started the Protein Structure Initiative, which seeks to increase knowledge of protein structure and has led to an increase in the number of know proteins structures. Unfortunately, even these efforts fall short as there are over 80,000 known protein structures but the function of many is completely unknown. The fledgling field of interface prediction seeks to use this wealth of structural information to be able to describe protein function and drastically increase our understanding of life processes.

Presented herein is a novel methodology for solving the protein-protein interface prediction problem leveraging a variety of Computer Science techniques. Specifically detailed is a process for decomposing this 3-dimensional problem into a feature extraction and classification problem using algorithms from computer vision and machine learning.

Major Advisor: Mike Bailey
Committee: Sinisa Todorovic
Committee: Ron Metoyer
Committee: Victor Hsu
GCR: Michael Scott 


Kelley Engineering Center (campus map)
1007
Nicole Thompson
1 541 737 3617
Nicole.Thompson at oregonstate.edu
Sch Elect Engr/Comp Sci
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