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A comment on Nucleotide Transformer: building robust foundation models for human genomics. Parent comment

Re:Nucleotide Transformer: building robust foundation models... by mbreese on Saturday December 07, 2024 @01:51PM (#42351857)
> from just the sequence and no other data

This is my real question with these... we already have a ton of other data for genomics. So, many of the important regions are already known and studied. And really, the functional importance of any given region/sequence is highly context/cell type specific. So, given this, what are the use cases? What kind of hypothesis generation can these models lead to that we aren't currently doing in genomics?

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Re:Nucleotide Transformer: building robust foundation models... by dekhn on Saturday December 07, 2024 @07:22PM (#42353971)
The whole idea of unsupervised learning is to find patterns in the data that people wouldn't have easily found by manually looking for categories/labels. So far most of the categories we've identified and manually clustered (to build statistical models that find more of them) have taken extensive discovery biology and curation efforts.
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