the field is the application of machine learning to biology (specifically drug design, but also the wider area of computational biology in all its forms).
Here's some of my prior work: https://arxiv.org/abs/1502.02072 however that doesn't use transformers. The DeepMind work on protein structure prediction does, and it represents one of the greatest technical achievements of the modern era.
Transformers basically took anything that was "sequence learning" (large fractions of computational biology are) and made it work 100X better over night.
Thank you for clarifying. I see that the paper has six authors two of whom
declare equal contribution. Could you please further clarify what was your
personal contribution to the paper (to the extent that this doesn't unecessarily
expose your personal information)?
Regarding Transformers, the results on protein structure prediction are
certainly impressive, but they are not enough to justify your comment that
"transformers have literally transformed science". At most we can tell that they
have considerably improved protein structure prediction. Perhaps your comment
was an exaggeration?
Edit: I can't find the paper on the ICML 2015 website, although I can see that
it has a few hundred citations, as a preprint, which is not uncommon these days.
But, could you point to some published work you contributed to?
Transformers basically took anything that was "sequence learning" (large fractions of computational biology are) and made it work 100X better over night.