Timothy Kunz honored as the recipient of the 2017 Fred Wedler Outstanding Undergraduate Dissertation Award

July 10, 2017 – Timothy Kunz, a recent graduate of Penn State’s Biochemistry and Molecular Biology Program, was honored as the recipient of the 2017 Fred Wedler Outstanding Undergraduate Dissertation Award.  Kunz received notification on April 26, 2017.

Each year, the Department of Biochemistry and Molecular Biology, selects one undergraduate student to receive the award which is given to the student whose dissertation is judged to be the best, based on evaluation criteria given to a group of honors advisors.  The award carries a cash prize and in addition Kunz’s name will be engraved on the Wedler Award plaque.

When asked why he decided to focus on a career in microbiology Kunz said that he enjoyed both chemistry and biology in high school and that he decided to major in biochemistry because it was a mix of the two.  It was the positive experiences Kunz had in his microbiology courses that made him realize that molecular biology would be the path his career would eventually take.  Kunz had the opportunity to join the Schreyer Honors College through the Gateway Program, an opportunity that he credits with providing substantial monetary and academic support.  It was through his involvement with the Schreyer Honors College that he was able to secure funding that allowed him to stay in State College the last two summers prior to his graduation and continue his academic work.

Kunz also secured a position in the Mahony Laboratory while at Penn State.  The Mahony Laboratory is a computational biology laboratory focused on developing machine-learning approaches for understanding gene regulation.  The laboratory’s primary focus is transcription factor binding data, but also investigates other high-throughput sequencing data such as; Hi-C, RNA and DNase.

Kunz’s dissertation focused on Hi-C data.  The focus of his research was to develop a novel approach to chromatin interaction analysis based on the Self-Organizing Map (SOM) Algorithm.  This approach gives a more intuitive visualization of the data and serves as a platform for assessing correlations between various genomic activities and chromatin structure. The SOM algorithm provides a two-dimensional grid on which chromatin interactions indicated in Hi-C data are visualized. The resulting data structure can then be used to assess the relationships between genomic biochemical activities (e.g. transcription, histone modifications, protein-DNA binding, etc.) and the organization of the chromatin. Given a set of genomic coordinates corresponding to a given biochemical activity, the degree to which this activity is segregated or compartmentalized in chromatin interaction space can be intuitively visualized on the SOM grid and quantified using modified Lorenz curve analysis.  Kunz said they were able to demonstrate the utility of the approach for exploratory analysis of genome compartmentalization using human high-resolution Hi-C datasets.

In summary Kunz developed a novel approach to visualizing chromatin interaction data on a 2D grid using the implementation of the Self-Organizing Map algorithm. This approach allows for efficient and intuitive visualizations and quantifications of the distribution and segregation of biochemical activities in chromatin interaction space. The utility of this method has been demonstrated using human Hi-C data and exploring the distribution of ChIP-seq data.  Kunz hopes that this software will be useful in future analyses of chromatin organization and compartmentalization.

Kunz plans to continue his education and pursue his Ph. D. and has accepted a Research Assistant positon in the Melton Lab at Harvard University.  The Melton Lab focuses on Type 1 Diabetes, utilizing stem cells and mouse models.  There Kunz will be working under the direction of Dr. Jose Rivera-Feliciano.