Modeling Protein Data
The scale of data in protein modeling is significantly smaller than in NLP or computer vision, making it essential to incorporate various priors—be they physical, biological, or chemical—into the modeling process. As the conversation shifts to predicting clinical outcomes, the challenge of managing large input sizes, such as entire genomes combined with clinical histories, highlights the need for continued advancements in handling extensive data inputs.In this clip
From this podcast
Gradient Dissent - A Machine Learning Podcast
Accelerating drug discovery with AI: Insights from Isomorphic Labs
Related Questions