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A socratic dialogue over the utility of DNA language models (Part 2 of 2)

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I am aware that DNA language models are useful for things other than those two (like protein fitness), but variant prediction and genome generation are the two bits that I find most interesting. Twitter link for this article. (The Introduction is a repeat from Part 1. Skip it if you’ve already read it!) I think I, alongside many other people in this field, live in this seemingly parallel universe where we don’t really understand why anyone is working on DNA language models. I say ‘parallel’, because there is obviously a world in which some very smart people are very much bullish about them: specifically the Arc Institute. Who, just yesterday, released a paper that many people are quite excited about: Evo 2, a successor to the original Evo model. From the news article: Arc Institute researchers have developed a machine learning model called Evo 2 that is trained on the DNA of over 100,000 species across the entire tree of life. Its deep understanding of biological code means that Evo 2

Introduction The dialogue Part 1 is focused on variant pathogenicity prediction using these models. Part 2 is focused on genome generation using these models. I am aware that DNA language models are useful for things other than those two (like protein fitness), but variant prediction and genome generation are the two bits that I find most interesting. Twitter link for this article. (The Introduction is a repeat from Part 1. Skip it if you’ve already read it!) I think I, alongside many other people in this field, live in this seemingly parallel universe where we don’t really understand…

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