Youtor
Training Evaluating and Understanding Evolutionary Models for Protein Sequences
>> YOUR LINK HERE: ___ http://youtube.com/watch?v=hcJS9d09ECA
PhD Dissertation Talk. Covers work on using methods from natural language processing, specifically large scale language models, for learning representations of protein sequences. • Papers covered: • Evaluating Protein Transfer Learning with TAPE (https://www.biorxiv.org/content/10.11...) • Transformer protein language models are unsupervised structure learners (https://www.biorxiv.org/content/10.11...) • MSA Transformer (https://www.biorxiv.org/content/10.11...) • Language models enable zero-shot prediction of the effects of mutations on protein function (https://www.biorxiv.org/content/10.11...) • Timestamps: • 0:00 - Intro • 0:56 - Evolutionary Models • 11:06 - Neural Evolutionary Models • 13:25 - Evaluating Protein Transfer Learning with TAPE • 15:58 - Transformer protein language models are unsupervised structure learners • 26:18 - MSA Transformer • 33:48 - Language models enable zero-shot prediction of the effects of mutations on protein function • 42:30 - Future Work • 46:42 - Conclusion • 47:15 - Thank yous • 50:21 - Q A • Thank you very much to my advisors, John Canny and Pieter Abbeel, and to everyone who helped along the way!
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