Person
John Jumper
John Jumper is a scientist at Google DeepMind who led the development of AlphaFold, the system that predicts a protein's three-dimensional structure from its amino-acid sequence — a problem that had previously required years of laboratory work for a single structure. AlphaFold's freely available database has been used by millions of researchers across biology and drug discovery. In 2024 he shared the Nobel Prize in Chemistry with DeepMind chief executive Demis Hassabis for the work, alongside David Baker, one of two AI-linked science Nobels announced in the same week. The award was widely read as a signal that machine-learning methods had come to be recognised as science in their own right.
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- Models & capabilities 2
- Culture & impact 1
- Benchmarks & progress 1
Hassabis and Jumper share the Nobel Prize in Chemistry
Half the prize went to Baker for computational protein design; the other half was split between Hassabis and Jumper for AlphaFold's structure prediction.
Culture & impact
AlphaFold 2 solves protein structure prediction at CASP14
DeepMind's system predicted protein structures to roughly experimental accuracy, ending a fifty-year-old open problem in biology.
Models & capabilities · Benchmarks & progress
DeepMind publishes early AlphaFold protein structure work
Describes the CASP13-winning system, which used deep networks trained on genomic data to predict inter-residue distances rather than folding a structure directly.
Models & capabilities
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Referenced in passing — John Jumper isn't the main subject of these.