Improved protein structure prediction using potentials from deep learning-Reference-Cited by-同舟云学术

Improved protein structure prediction using potentials from deep learning

Published:2020-01-15 Issue:7792 Volume:577 Page:706-710
ISSN:0028-0836
Container-title:Nature
language:en
Short-container-title:Nature

Author:

Senior Andrew W.,Evans Richard,Jumper John,Kirkpatrick James,Sifre Laurent,Green Tim,Qin Chongli,Žídek Augustin,Nelson Alexander W. R.,Bridgland Alex,Penedones Hugo,Petersen Stig,Simonyan Karen,Crossan Steve,Kohli Pushmeet,Jones David T.,Silver David,Kavukcuoglu Koray,Hassabis Demis

Publisher

Springer Science and Business Media LLC

Subject

Multidisciplinary

Link

http://www.nature.com/articles/s41586-019-1923-7.pdf

Reference55 articles.

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3. Schaarschmidt, J., Monastyrskyy, B., Kryshtafovych, A. & Bonvin, A. M. J. J. Assessment of contact predictions in CASP12: co-evolution and deep learning coming of age. Proteins 86, 51–66 (2018).

4. Kirkwood, J. Statistical mechanics of fluid mixtures. J. Chem. Phys. 3, 300–313 (1935).

5. Kryshtafovych, A., Schwede, T., Topf, M., Fidelis, K. & Moult, J. Critical assessment of methods of protein structure prediction (CASP)—Round XIII. Proteins 87, 1011–1020 (2019).

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