Bjorn Bean

Background

About Bjorn Bean

I believe that understanding biological systems and applying that knowledge will allow us to tackle current medical, environmental and energy challenges. This has driven me to spend over a decade studying and working in the field of molecular biology. My journey started by studying cancer cell morphology and invasion in the Roberge lab (UBC) and optimizing liquid chromatography-mass spectrometry protocols at Environment and Climate Change Canada. But when I started to learn about the incredible insights we can gain from using yeast as a model organism I decided to pursue a doctorate in the Conibear lab (UBC). Here I leveraged our knowledge of yeast genetics and our ability to conduct high-throughput imaging-based screens to learn about cellular membrane trafficking systems and how their dysfunction is linked to neurodegenerative and diseases. Next, I joined the Martin and Whiteway labs (Concordia University) as a postdoctoral fellow to apply my knowledge of yeast genetics in the field of synthetic biology. In this position I have developed a new CRISPR-Cas9 toolkit and engineered the yeast sterol biosynthetic pathway to produce the human sterol cholesterol, enabling us to produce an array of sensitive new opioid biosensors. Now at BenchSci I'm helping translate the biology knowledge I've gained into machine learning and large language model-based AI systems. These systems can extract granular pieces of knowledge from scientific literature and stitch them together to answer a wide array of questions. They can also ask their own questions which enables deep dives into data. I'm inspired by the potential of these tools to accelerate research. I'm also inspired by the quality of scientists and engineers that I have the privilege of working with.