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Augmented Data For Stanford Covid Vaccine

Augmented Data for Stanford Covid Vaccine

@kaggle.mathurinache_augmented_data_for_stanford_covid_vaccine

About this Dataset

Augmented Data For Stanford Covid Vaccine

data augmentation comes from many iterations of this excellent script https://www.kaggle.com/its7171/how-to-generate-augmentation-data

About this competition,
Winning the fight against the COVID-19 pandemic will require an effective vaccine that can be equitably and widely distributed. Building upon decades of research has allowed scientists to accelerate the search for a vaccine against COVID-19, but every day that goes by without a vaccine has enormous costs for the world nonetheless. We need new, fresh ideas from all corners of the world. Could online gaming and crowdsourcing help solve a worldwide pandemic? Pairing scientific and crowdsourced intelligence could help computational biochemists make measurable progress.

mRNA vaccines have taken the lead as the fastest vaccine candidates for COVID-19, but currently, they face key potential limitations. One of the biggest challenges right now is how to design super stable messenger RNA molecules (mRNA). Conventional vaccines (like your seasonal flu shots) are packaged in disposable syringes and shipped under refrigeration around the world, but that is not currently possible for mRNA vaccines.

Researchers have observed that RNA molecules have the tendency to spontaneously degrade. This is a serious limitation--a single cut can render the mRNA vaccine useless. Currently, little is known on the details of where in the backbone of a given RNA is most prone to being affected. Without this knowledge, current mRNA vaccines against COVID-19 must be prepared and shipped under intense refrigeration, and are unlikely to reach more than a tiny fraction of human beings on the planet unless they can be stabilized.

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