Deep learning models for predicting RNA degradation via dual crowdsourcing

Hannah K. Wayment-Steele, Wipapat Kladwang, Andrew M. Watkins, Do Soon Kim, Bojan Tunguz, Walter Reade, Maggie Demkin, Jonathan Romano, Roger Wellington-Oguri, John J. Nicol, Jiayang Gao, Kazuki Onodera, Kazuki Fujikawa, Hanfei Mao, Gilles Vandewiele, Michele Tinti, Bram Steenwinckel, Takuya Ito, Taiga Noumi, Shujun He, Keiichiro Ishi, Youhan Lee, Fatih Öztürk, King Yuen Chiu, Emin Öztürk, Karim Amer, Mohamed Fares, Unknown, Rhiju Das

Open source

DOI: 10.1038/s42256-022-00571-8
Published: 2022-12-14
Container: Nature Machine Intelligence
Publisher: Springer Science and Business Media LLC
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.1038/s42256-022-00571-8,
  title = {Deep learning models for predicting RNA degradation via 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 Öztürk and King Yuen Chiu and Emin Öztürk and Karim Amer and Mohamed Fares and Unknown and Rhiju Das},
  year = {2022},
  journal = {Nature Machine Intelligence},
  doi = {10.1038/s42256-022-00571-8},
  url = {https://doi.org/10.1038/s42256-022-00571-8}
}

RIS

TY  - JOUR
TI  - Deep learning models for predicting RNA degradation via dual crowdsourcing
AU  - Hannah K. Wayment-Steele
AU  - Wipapat Kladwang
AU  - Andrew M. Watkins
AU  - Do Soon Kim
AU  - Bojan Tunguz
AU  - Walter Reade
AU  - Maggie Demkin
AU  - Jonathan Romano
AU  - Roger Wellington-Oguri
AU  - John J. Nicol
AU  - Jiayang Gao
AU  - Kazuki Onodera
AU  - Kazuki Fujikawa
AU  - Hanfei Mao
AU  - Gilles Vandewiele
AU  - Michele Tinti
AU  - Bram Steenwinckel
AU  - Takuya Ito
AU  - Taiga Noumi
AU  - Shujun He
AU  - Keiichiro Ishi
AU  - Youhan Lee
AU  - Fatih Öztürk
AU  - King Yuen Chiu
AU  - Emin Öztürk
AU  - Karim Amer
AU  - Mohamed Fares
AU  - Unknown
AU  - Rhiju Das
PY  - 2022
JO  - Nature Machine Intelligence
DO  - 10.1038/s42256-022-00571-8
UR  - https://doi.org/10.1038/s42256-022-00571-8
ER  -

APA

Wayment-Steele, H. K., Kladwang, W., Watkins, A. M., Kim, D. S., Tunguz, B., Reade, W., Demkin, M., Romano, J., Wellington-Oguri, R., Nicol, J. J., Gao, J., Onodera, K., Fujikawa, K., Mao, H., Vandewiele, G., Tinti, M., Steenwinckel, B., Ito, T., Noumi, T., He, S., Ishi, K., Lee, Y., Öztürk, F., Chiu, K. Y., Öztürk, E., Amer, K., Fares, M., Unknown, & Das, R. (2022). Deep learning models for predicting RNA degradation via dual crowdsourcing. Nature Machine Intelligence. https://doi.org/10.1038/s42256-022-00571-8

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crossref · retrieved 2026-09-26T14:35:47.344Z