[biomcgary]

In biology, the most important step is finding the right thing to measure. Biological systems are highly contextual, so the second most important step is finding the second thing to measure in relationship to the first thing.

In the case of AlphaFold, measuring crystal structures is the most important thing (molecular phenotype). The second most important thing is measuring many genomes. Multiple sequence alignments allows evolution (variation under selection) to tell you about the important bits of the structure. The distance from aligned DNA sequences to protein structure isn't a bridge too far.

Unfortunately, biology has been mislead by the popularity of transcriptomics, which the post touches on briefly (limits of single-cell approaches). Transcriptomics generates lots of data (relatively) cheaply, but isn't really the right thing to measure most of the time because it is too far removed causally from the organismal phenotype, the thing we generally care about in biomedicine. Although gene expression has provided some insights, we've exhausted most of its value by now and I doubt ML will rescue it (speaking from personal experience).