Student Testimonials

“I would recommend the Bioinformatics program at the University of Guelph to anyone with a genuine interest in applying computational and statistical tools to address fundamental questions in biology. The program is tailored to students with diverse academic backgrounds. Small class sizes allowed for maximal interaction with students and faculty, primarily through presentations. Classes were very hands-on, covering a wide variety of theoretical and applied topics including microarray analysis and DNA sequencing, which I thoroughly enjoyed. In the course of completing my Masters degree in Bioinformatics, I had the opportunity to conduct my summer project in the field of biodiversity informatics, where I developed an interest in DNA barcoding. After completing my degree, I collaborated with my advisor on a publication of my work. Currently, I am continuing my Masters work as a PhD student at the University of Guelph under the supervision of my Masters advisor.”

Jarrett Philips, MBINF ‘14

“My bioinformatics degree has dramatically improved my awareness to how much computation goes into research, and to how great a role "Big Data" will play in pursuits such as personalized medicine. Now as a medical student, I can appreciate the process of how a tissue sample can tell what treatments to use for patients. It has also provided me with the skills to better understand scientific research, from multivariable analysis to the assembly of genomes.”

Andrew Shure, MBINF ‘15

“The bioinformatics program engages faculty from different colleges across the campus to teach and advise students. As a result, there is a well-structured curriculum that covers computational statistics, genomics and computer sciences. Each student is advised by two experts, a biologist and a computational scientist or a computational statistician. This allows for collaborative research and a wonderful opportunity to develop strong interdisciplinary networks. I believe that the combination of core coursework, comprehensive exam, and participation in interdisciplinary research has given me a depth of knowledge and skills needed to develop a successful research career. Now I feel confident to solve real-life machine learning problems and take on leadership roles.”

Anjali Silva, MBINF ’13 and current PhD student

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