Accurate proteome-wide missense variant effect prediction with AlphaMissense
Jun Cheng(Google DeepMind (United Kingdom)), Žiga Avsec(Google DeepMind (United Kingdom)), Pushmeet Kohli(Google (United Kingdom)), Taylor Applebaum(Google DeepMind (United Kingdom)), Tobias Sargeant(Google DeepMind (United Kingdom)), Guido Novati(Google DeepMind (United Kingdom)), John Jumper(Google DeepMind (United Kingdom)), Alexander Pritzel(Google DeepMind (United Kingdom)), Rosalia G. Schneider(Google DeepMind (United Kingdom)), Andrew Senior(Google DeepMind (United Kingdom)), Clare Bycroft(Google DeepMind (United Kingdom)), Akvilė Žemgulytė(Google DeepMind (United Kingdom)), Michal Zielinski(Google DeepMind (United Kingdom)), Lai Hong Wong(Google DeepMind (United Kingdom)), Joshua Pan(Google DeepMind (United Kingdom)), Demis Hassabis(Google DeepMind (United Kingdom))
Cited by 2,004
Related Papers
Human-level control through deep reinforcement learning
|Nature|2015|29.9k
AlphaFold Protein Structure Database: massively expanding the structural coverage of protein-sequence space with high-accuracy models
|Nucleic Acids Research|2021|8.2k
Highly accurate protein structure prediction for the human proteome
|Nature|2021|3.2k
International evaluation of an AI system for breast cancer screening
|Nature|2020|3.1k