• Corpus ID: 238856802

Predictive models of RNA degradation through dual crowdsourcing

@article{WaymentSteele2021PredictiveMO,
  title={Predictive models of RNA degradation through dual crowdsourcing},
  author={Hannah K. Wayment-Steele and Wipapat Kladwang and Andrew M. Watkins and Do Soon Kim and Bojan Tunguz and Walter Reade and Maggie Demkin and Jonathan Romano and Roger Wellington-Oguri and John J. Nicol and Jiayang Gao and Kazuki Onodera and Kazuki Fujikawa and Hanfei Mao and Gilles Vandewiele and Michele Tinti and Bram Steenwinckel and Takuya Ito and Taiga Noumi and Shujun He and Keiichiro Ishi and Youhan Lee and Fatih {\"O}zt{\"u}rk and Anthony Chiu and Emin {\"O}zt{\"u}rk and Karim Amer and Mohamed Fares and Eterna Participants and Rhiju Das},
  journal={ArXiv},
  year={2021}
}
Messenger RNA-based medicines hold immense potential, as evidenced by their rapid deployment as COVID-19 vaccines. However, worldwide distribution of mRNA molecules has been limited by their thermostability, which is fundamentally limited by the intrinsic instability of RNA molecules to a chemical degradation reaction called in-line hydrolysis. Predicting the degradation of an RNA molecule is a key task in designing more stable RNA-based therapeutics. Here, we describe a crowdsourced machine… 

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