Wikipedia

John M. Jumper

(Redirected from John Jumper (AI researcher))
For other people named John Jumper, see John Jumper (disambiguation).

John Michael Jumper (born 1985)[1] is an American chemist and computer scientist. He currently serves as director at Google DeepMind.[2][3][4] Jumper and his colleagues created AlphaFold,[5] an artificial intelligence (AI) model to predict protein structures from their amino acid sequence with high accuracy.[6] Jumper stated that the AlphaFold team plans to release 100 million protein structures.[7]

John Jumper
Jumper in 2024
Born
John Michael Jumper

1985 (age 38–39)[1]
Little Rock, Arkansas, U.S.[1]
Education
Known forAlphaFold
AwardsNature's 10 (2021)
BBVA Foundation Frontiers of Knowledge Award (2022)
Breakthrough Prize in Life Sciences (2023)
Nobel Prize in Chemistry (2024)
Scientific career
FieldsArtificial intelligence
Machine learning
InstitutionsGoogle
DeepMind
ThesisNew methods using rigorous machine learning for coarse-grained protein folding and dynamics (2017)
Doctoral advisorTobin R Sosnick
Karl Freed

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.[6][8] Jumper and Demis Hassabis were awarded half of the 2024 Nobel Prize in Chemistry for protein structure prediction.[9][10]

Education

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Jumper received a Bachelor of Science with majors in physics and mathematics from Vanderbilt University in 2007,[11] a Master of Philosophy in theoretical condensed matter physics from the University of Cambridge in 2010 on a Marshall Scholarship,[12] a Master of Science in theoretical chemistry from the University of Chicago in 2012, and a Doctor of Philosophy in theoretical chemistry from the University of Chicago in 2017.[13] His doctoral advisors at the University of Chicago were Tobin R. Sosnick and Karl Freed.[14]

Career

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Jumper's research investigates algorithms for protein structure prediction.[2]

AlphaFold

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See also: AlphaFold and Protein structure prediction
 
This image represents the final product of AlphaFold and it compares its results with other competitors at the CASP competition.

AlphaFold[5][15] is a deep learning algorithm developed by Jumper and his team at DeepMind, a research lab acquired by Google's parent company Alphabet Inc. It is an artificial intelligence program which performs predictions of protein structure.[16]

Awards and honors

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In November 2020, AlphaFold was named the winner of the 14th Critical Assessment of Structure Prediction (CASP) competition.[17][18][19] This international competition benchmarks algorithms to determine which one can best predict the 3D structure of proteins. AlphaFold won the competition, outperforming other algorithms scoring above 90 for around two-thirds of the proteins in CASP's global distance test (GDT), a test that measures the degree to which a computational program predicted structure is similar to the lab experiment determined structure, with 100 being a complete match, within the distance cutoff used for calculating GDT.[20][21]

In 2021, Jumper was awarded the BBVA Foundation Frontiers of Knowledge Award in the category "Biology and Biomedicine".[22] In 2022 Jumper received the Wiley Prize in Biomedical Sciences[23] and for 2023 the Breakthrough Prize in Life Sciences for developing AlphaFold, which accurately predicts the structure of a protein.[24] In 2023 he was awarded the Canada Gairdner International Award[25] and the Albert Lasker Award for Basic Medical Research.[26]

In 2024, Jumper and Demis Hassabis shared half of the Nobel Prize in Chemistry for their protein folding predictions, the other half went to David Baker for computational protein design.[9][10]

References

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  1. ^ a b c "John M. Jumper: Facts". The Nobel Prize. Nobel Prize Outreach AB. 2024. Retrieved October 9, 2024.
  2. ^ a b John M. Jumper publications indexed by Google Scholar  
  3. ^ John M. Jumper publications from Europe PubMed Central
  4. ^ Eisenstein, Michael (2021). "Artificial intelligence powers protein-folding predictions". Nature. 599 (7886). Springer Nature: 706–708. doi:10.1038/d41586-021-03499-y. S2CID 244528561. Retrieved December 24, 2021.
  5. ^ a b John Jumper; Richard Evans; Alexander Pritzel; et al. (July 15, 2021). "Highly accurate protein structure prediction with AlphaFold". Nature. Bibcode:2021Natur.596..583J. doi:10.1038/S41586-021-03819-2. ISSN 1476-4687. PMC 8371605. Wikidata Q107555821.
  6. ^ a b Maxmen, Amy (2021). "Nature's 10: John Jumper: Protein predictor". Nature. 600 (7890). Springer Nature: 591–604. doi:10.1038/d41586-021-03621-0. PMID 34912110. S2CID 245256541.
  7. ^ Browne, Grace (2021). "DeepMind's AI has finally shown how useful it can be". wired.com. Retrieved December 24, 2021.
  8. ^ John M. Jumper on LinkedIn  
  9. ^ a b "The Nobel Prize in Chemistry 2024". Nobel Media AB. Retrieved October 9, 2024.
  10. ^ a b "Press release: The Nobel Prize in Chemistry 2024". NobelPrize.org. Retrieved October 9, 2024.
  11. ^ Doster, Stephen. "John Jumper, developer of AlphaFold, to present an Apex Lecture on August 30". Vanderbilt University. Retrieved October 9, 2024.
  12. ^ "University of Cambridge alumni awarded 2024 Nobel Prize in Chemistry | University of Cambridge". www.cam.ac.uk. October 9, 2024. Retrieved October 9, 2024.
  13. ^ "UChicago alum John Jumper shares Nobel Prize for model to predict protein structures | University of Chicago News". news.uchicago.edu. October 9, 2024. Retrieved October 9, 2024.
  14. ^ Jumper, John Michael (2017). New methods using rigorous machine learning for coarse-grained protein folding and dynamics. chicago.edu (PhD thesis). University of Chicago. doi:10.6082/M1BZ647N. OCLC 1237239279. ProQuest 1883866286.
  15. ^ Andrew W Senior; Richard Evans; John Jumper; et al. (January 15, 2020). "Improved protein structure prediction using potentials from deep learning". Nature. 577 (7792): 706–710. doi:10.1038/S41586-019-1923-7. ISSN 1476-4687. PMID 31942072. Wikidata Q92669549.
  16. ^ "AlphaFold". Deepmind. Retrieved November 30, 2020.
  17. ^ "AlphaFold: a solution to a 50-year-old grand challenge in biology". Deepmind. November 30, 2020. Retrieved November 30, 2020.
  18. ^ Sample, Ian (December 2, 2018). "Google's DeepMind predicts 3D shapes of proteins". The Guardian. Retrieved November 30, 2020.
  19. ^ Shead, Sam (November 30, 2020). "DeepMind solves 50-year-old 'grand challenge' with protein folding A.I." CNBC. Retrieved November 30, 2020.
  20. ^ "DeepMind's protein-folding AI has solved a 50-year-old grand challenge of biology". MIT Technology Review. Retrieved November 30, 2020.
  21. ^ Robert F. Service, 'The game has changed.' AI triumphs at solving protein structures, Science, November 30, 2020
  22. ^ "BBVA Foundation Frontiers of Knowledge Award 2022". frontiersofknowledgeawards-fbbva.es.
  23. ^ "Wiley Prize 2022". wiley.com.
  24. ^ "Breakthrough Prizes 2023". breakthroughprize.org. Retrieved September 22, 2022.
  25. ^ Foundation, The Gairdner (March 30, 2023). "2023 Canada Gairdner Award Winners Announced". The Gairdner Foundation. Retrieved October 9, 2024.
  26. ^ Admin, Lasker. "AlphaFold—for predicting protein structures". Lasker Foundation. Retrieved October 9, 2024.
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