Deep Learning in Biomolecular Research:  A Focus on what it is, how it can be used and Implementation Challenges

Katharine Michie1

1Australian scientist specializing in structural biology, biochemistry, and biophysics

Biography:

Dr. Katharine Michie is an Australian scientist specializing in structural biology, biochemistry, and biophysics, serves as the Chief Scientist of the Structural Biology Facility at UNSW. Kate trained in protein chemistry and biophysics (PhD, USYD) before transitioning to structural biology during two fellowships (Marie Curie and UNESCO L’Oréal) at the MRC Laboratory of Molecular Biology, Cambridge, UK. Kate currently is focused on advancing research through facilitating the adoption of Deep Learning technology into structural biology and molecular biological science more broadly. She envisions a future where AI-driven insights that are revolutionizing structural biology benefit both scientific discovery and medical applications.

Abstract:

The popular press is screaming about ‘AI’, from everything from chatbots to image generation–you’d be forgiven if you thought it’s all hype. But, is it? Follow this adventure as we work through what Deep Learning has done for molecular science (think Alphafold but there is a lot more to the story than this), the science behind it, how it is being used, the impacts it’s making and the difficulties in making it easy for researchers to access. (Don’t worry, Biology 101 is provided). 

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