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Biology Student Builds Computational Skills for Modeling and Data Analysis

Eight months before defending her dissertation on the effects of genetic variation on signaling dynamics, Biology student Selcan Aydin spent two weeks in San Diego building skills needed for the modeling and data analysis challenges of her research.

She was among 19 Duke students who received Graduate Student Training Enhancement Grants (GSTEG) in 2016-17 for training beyond their core disciplines. Her faculty mentor was Nicolas Buchler. Recently Dr. Aydin reflected on her experience:

I attended the Computational Synthetic Biology Track of the Quantitative Biology (Qbio) Summer School, organized by the University of California, San Diego. This was a two-week professional workshop dedicated to the advancement of quantitative biology.

The workshop focused on different modeling approaches where experts in the field gave lectures in the morning, followed by hands-on training sessions in the afternoon. Attending the workshop allowed me to learn new modeling and data analysis methods that were useful for advancing my dissertation research.

In addition to learning new skills, I was exposed to cutting-edge research via seminars given by various experts in the Qbio field.

Finally, the group project I did with fellow trainees was very helpful in gaining hands-on mathematical modeling experience where I had the chance to interact with computational biologists. This allowed me to improve my collaboration and scientific communication skills in addition to the scientific knowledge I have gained in computational and mathematical modeling.

This internal funding mechanism from the Office of the Vice Provost for Interdisciplinary Studies encourages graduate students to step away from their core research and training to acquire skills, knowledge or co-curricular experiences that will give them new perspectives on their research agendas. Graduate Student Training Enhancement Grants are intended to deepen preparation for academic positions and other career trajectories.

Image: Selcan Aydin (far right) and her fellow trainees on the last day of Quantitative Biology (Qbio) Summer School 2016