Скачать с ютуб Discrete diffusion models for generative protein design в хорошем качестве

Discrete diffusion models for generative protein design

presented on by Sarah Alamdari on July 10th 20204 Abstract: Engineered proteins play increasingly essential roles in applications spanning pharmaceuticals, molecular tools, synthetic biology, and more. Deep generative models offer the ability to accelerate protein engineering for therapeutic and biological applications. Recently, a family of generative models called diffusion models has demonstrated the potential for unprecedented capability and control in de novo design. In this talk, we will discuss a general-purpose diffusion framework, EvoDiff, that combines evolutionary-scale data with the distinct conditioning capabilities of diffusion models for controllable protein design in sequence space alone. We envision that these modeling frameworks will enable new capabilities in protein engineering towards programmable, functional design.