Yan Zhang, Ph.D.
12
Chair
Dissertation Title
Research Interest
My project is to identify the large number of anomalous mass spectra including mutations, splice variants, post-translational modifications and unidentified genes. Most of these categories have been associated with diseases, such as cancer, various genetic diseases and diabetes. My goal is to develop new algorithms to cluster spectra into categories based on their similarities, which with other discriminators (topologies, mass defects, etc.) will lead to unambiguous identifications and assignment of functions to proteins and their genes. This project has several scientific or technological problems for me to solve: (1) The electrospray model used to simulate the fragmentation of peptides; (2) A statistical model for classifying the peak lists; (3) The computational efficiency problem that arises when processing the high throughput real data; (4) Noise filtering algorithms and false positive reduction method; (5) Protein structure prediction algorithms based on peptide topology information, etc. There are many feasible applications that can derive from this work and I have had some initial successes. For example, I have explored the use of statistical analysis to distinguish tagged and untagged data from MS, such as the use of isobaric isotope enriched chemical tags to reveal protein topology.