Statistical machine learning; biologically-inspired computer vision

M.Binf. ‘20

I was first introduced to the field of Bioinformatics during my undergraduate studies which motivated me to learn how to analyze biological data through computational methods. I completed my Master of Bioinformatics degree at the University of Guelph. The program taught me several concepts in Bioinformatics, which included programming in R and bash, Next-Generation Sequencing analyses, and statistical methods. Currently, I am a research assistant at the University of Toronto, where I analyze single cell RNA-sequencing data from control and stroke-induced brains from mice to study the temporal and spatial changes within their transcriptomes. Ultimately, the program prepared me not only for expanding my skills as a bioinformatician, but also prepared me for the work force and building my career. I am very thankful for completing my Master’s degree at the University of Guelph because it prepared me for success.

Protein homeostasis; Mycobacterium tuberculosis; ESI-MS; high-field NMR spectroscopy

Wine yeasts; metabolomics; vinification