Data-efficient Deep Learning to Better Model Emerging Biology
The COVID-19 outbreak offers a solemn reminder of how little we know - and how little data we have - for emerging biology. Novel, data-efficient learning algorithms are needed for these types of data poor environments. InVivo AI is developing novel algorithms capable of learning from small and noisy biological datasets. In light of the COVID-19 outbreak, the startup is leveraging their platform to learn models for the discovery of novel drug and vaccine therapies. In this webinar, we will present some of the opportunities for AI to contribute to finding therapeutic solutions to the current and future pandemics.
Expert in machine learning and computational biology passionate about bridging the gap between the computational and life sciences. Before co-founding InVivo AI, Dr. Giguère has spent significant amounts of time working with research laboratories, pharmaceutical companies and hospital networks on projects including the use of machine learning for design of pharmaceutical compounds, the prediction of antigen recognition by the MHC pathway for vaccine and immunotherapy development, the prediction of protein-protein interactions and kinase phosphorylation for drug target identification, and the prediction of antimicrobial resistance for the treatment of multi-drug resistant infection.