Interesting results. Have you tried a train/test split where you hold out one protein family for validation, while training the model on the rest? e.g. train on all non-kinases, then validate on a kinase
Very nice! Do you think this predictive modeling can translate to small molecule metabolism? It seems like a logical step to me… if you can predict small molecule binding based on amino acid sequence and chemical formula, may you be able to go one step further and determine if that chemical formula is altered based on the binding event?
The dream is that we keep improving this general binding model, and then we can get smaller datasets and fine-tune on those problems. A model that truly learns how to think about how molecules and proteins interacts, should need less data to understand these similar tasks.
Interesting results. Have you tried a train/test split where you hold out one protein family for validation, while training the model on the rest? e.g. train on all non-kinases, then validate on a kinase
Epic
Very nice! Do you think this predictive modeling can translate to small molecule metabolism? It seems like a logical step to me… if you can predict small molecule binding based on amino acid sequence and chemical formula, may you be able to go one step further and determine if that chemical formula is altered based on the binding event?
The dream is that we keep improving this general binding model, and then we can get smaller datasets and fine-tune on those problems. A model that truly learns how to think about how molecules and proteins interacts, should need less data to understand these similar tasks.