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General:  covid Type:  dataset model Data Domain:  tabular Framework:  tensorflow
Abid 0f0352eac3
Data, Model and Submission added to DVC
2 years ago
69b9f8fb25
stop tracking Data
2 years ago
5b005d63fb
Complete project from Deepnote
2 years ago
69b9f8fb25
stop tracking Data
2 years ago
0f0352eac3
Data, Model and Submission added to DVC
2 years ago
0f0352eac3
Data, Model and Submission added to DVC
2 years ago
4379ac72a1
Initial commit
2 years ago
0f0352eac3
Data, Model and Submission added to DVC
2 years ago
98b6032b9a
Readme edits
2 years ago
0f0352eac3
Data, Model and Submission added to DVC
2 years ago
5b005d63fb
Complete project from Deepnote
2 years ago
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README.md

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mRNA-Vaccine-Degradation-Prediction

mrna stanford

Building Predictive Model

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 Stability of mRNA

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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About

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-fQ
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