John M. Jumper – Wikipedia

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John Michael Jumper is a senior research scientist at DeepMind Technologies.[4][5][6] Jumper and his colleagues created AlphaFold,[7] which uses artificial intelligence (AI) to predict protein structures from their amino acid sequence with high accuracy.[8] Jumper has stated that the AlphaFold team plans to release 100 million protein structures.[9] The scientific journal Nature included Jumper as one of the ten “people who mattered” in science in their annual listing of Nature’s 10 in 2021.[8][2]

Education[edit]

Jumper was educated at the University of Chicago where he was awarded a PhD in 2017 for research on using machine learning to predict protein folding supervised by Karl Freed.[3] Jumper also holds a Master of Philosophy (MPhil) degree in Physics from the University of Cambridge and a Bachelor of Science degree in Physics and Mathematics from Vanderbilt University.[1]

Career and research[edit]

Jumper’s research investigates algorithms for protein structure prediction.[4]

AlphaFold[edit]

this image represents the final product of AlphaFold and it compares its results with other competitors at the CASP competition

AlphaFold[7][10] is a machine learning algorithm developed by Jumper and his team at DeepMind, a research lab acquired by Google’s parent company Alphabet Inc. The algorithm is designed to help scientists understand how proteins fold. It does this by using artificial intelligence to analyze massive amounts of data, including protein sequences and 3D structures. The algorithm then uses this information to predict protein folding. This could help researchers develop new treatments for diseases and create new materials with unique properties.

Awards and honours[edit]

In 2022 Jumper received the Wiley Prize in Biomedical Sciences[11] and also the BBVA Foundation Frontiers of Knowledge Award in 2021 in the category “Biology and Biomedicine”.[12] In 2023 he received the Breakthrough Prize in Life Sciences for developing AlphaFold, which accurately predicts the structure of a protein.[13] In November 2020, AlphaFold was named the winner of the Critical Assessment of Structure Prediction (CASP) competition. This international competition benchmarks algorithms to determine which one can best predict the 3D structure of proteins. AlphaFold won the competition, out performing other algorithms and making it the first machine learning algorithm to be able to accurately predict the 3D structure of proteins. Jumper and his team are now[when?] working on improving the accuracy of AlphaFold. They’re also exploring ways to use AlphaFold to develop new treatments for diseases and create new materials with unique properties.

References[edit]


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