Deriving phenotype from genomics is partly a problem of data. To give a computer the best chance to definitively correlate phenotype with sequence, you need mil

Deriving phenotype from genomics is partly a problem of data. To give a computer the best chance to definitively correlate phenotype with sequence, you need millions to tens of millions to hundreds of millions of DNA sequences from unrelated individuals from every possible genetic lineage, and you'd also need objective analysis of phenotypes without cultural influence, ie someone who is boisterous in one culture would be normal in another culture, independent of the actual genetics. Computationally, this is statistical analysis, and I doubt that AI would be able to offer anything unique. Protein folding prediction, on the other hand, is more of a question of "where do you start to arrive at the answer most efficiently", and AI is well suited for this, and it would be much better than humans at prediction using methodologies and correlations far outside of human brain capability.