Crowdsourced mapping of unexplored target space of kinase inhibitors

Crowdsourced mapping of unexplored target space of kinase inhibitors

The IDG-DREAM Challenge carried out crowdsourced benchmarking of predictive algorithms for kinase inhibitor activities on unpublished data. This study provides a resource to compare emerging algorithms and prioritize new kinase activities to accelerate drug discovery and repurposing efforts.

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Auteurs principaux: Anna Cichońska, Balaguru Ravikumar, Robert J. Allaway, Fangping Wan, Sungjoon Park, Olexandr Isayev, Shuya Li, Michael Mason, Andrew Lamb, Ziaurrehman Tanoli, Minji Jeon, Sunkyu Kim, Mariya Popova, Stephen Capuzzi, Jianyang Zeng, Kristen Dang, Gregory Koytiger, Jaewoo Kang, Carrow I. Wells, Timothy M. Willson, The IDG-DREAM Drug-Kinase Binding Prediction Challenge Consortium, Tudor I. Oprea, Avner Schlessinger, David H. Drewry, Gustavo Stolovitzky, Krister Wennerberg, Justin Guinney, Tero Aittokallio
Format: article
Langue:EN
Publié: Nature Portfolio 2021
Sujets:
Science
Q
Accès en ligne:https://doaj.org/article/f21e267a1ae047ee9c1ecdf221b76214
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Résumé:The IDG-DREAM Challenge carried out crowdsourced benchmarking of predictive algorithms for kinase inhibitor activities on unpublished data. This study provides a resource to compare emerging algorithms and prioritize new kinase activities to accelerate drug discovery and repurposing efforts.

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