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Global models of gene expression for an entire cell are fairly distant at this point, but there is quite a bit of work into modeling transcriptional activity fr
by jashephe 5y ago
Global models of gene expression for an entire cell are fairly distant at this point, but there is quite a bit of work into modeling transcriptional activity from sequence. If you're interested in reading more, a relevant technology to search for would be the "Massively Parallel Reporter Assay", or MPRA, which couples pools of 10⁴–10⁵+ synthetic DNA sequences with RNA sequencing to measure transcriptional output. Data from MPRA experiments is being used to train models, although these models are not anywhere near a point where you could model the gene expression of all regulatory elements in a cell; they are usually focused on a specific factor or regulatory sequence.
- sooheon 5y agoNotably DeepMind had a recent paper on using transformers to predict long range interactions in gene expression: https://www.nature.com/articles/s41592-021-01252-x https://www.nature.com/articles/s41592-021-01252-x
- chaxor 5y agoThe "train models" or ML portion is what I'm disappointed with unfortunately. I make ML models to predict things from genetic information somewhat regularly, but we all are aware of the enormous issues with that. I am more interested in the ab initio methods, as I have seen them be spectacularly useful in other fields - like Bethe salpeter equations in condensed matter physics.