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We need to design the model that will predict likely degradation rates at each base of an RNA molecule, trained on a subset of an Eterna dataset comprising over 3000 RNA molecules (which span a panoply of sequences and structures) and their degradation rates at each position.
Improving the stability of mRNA vaccines was a problem that was being explored before the pandemic but was expected to take many years to solve.Now, we must solve this deep scientific challenge in months, if not weeks, to accelerate mRNA vaccine research and deliver a refrigerator-stable vaccine against SARS-CoV-2, the virus behind COVID-19.
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I have experimented with multiple traditional models including Light GBM, Catboost, and BiLSTM, but the result was quite bad as compare to triple GRU layers. Using simple 3 Bidirectional GRU layer with linear activation. This model is quite simple and derived from xhlulu initial model.
https://deepnote.com/@abid/mRNA-Vaccine-Degradation-Prediction-ZbqWvkGcQXGU3-1fDqb-fQAre you sure you want to delete this access key?
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