I do think however that protein folding is very much understudied in the ML community, relative to say the big three of vision, NLP, and speech. The lack of standardized data sets and benchmarks, not to mention the need for domain knowledge, have made it difficult to get into the field
The PDB represents the best we have, but I wouldn't call it a great dataset for learning. The 150,000 known structures are a drop in the ocean when it comes to the space of possible sequences/structures.
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lol what-I was looking at this list of people who do this-in fact a lot of them ARE machine learning researchers...including some in my department!
I do think however that protein folding is very much understudied in the ML community, relative to say the big three of vision, NLP, and speech. The lack of standardized data sets and benchmarks, not to mention the need for domain knowledge, have made it difficult to get into the field
at the risk of offending NLPers/Vision/Speech I just think those tasks are 'easier' in a variety of ways.
CASP is a pretty nice dataset, so is all of the PDB.
The PDB represents the best we have, but I wouldn't call it a great dataset for learning. The 150,000 known structures are a drop in the ocean when it comes to the space of possible sequences/structures.