Complementing machine learning‐based structure predictions with native mass spectrometry-Reference-Cited by-同舟云学术

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Complementing machine learning‐based structure predictions with native mass spectrometry

Published:2022-05-21 Issue:6 Volume:31 Page:
ISSN:0961-8368
Container-title:Protein Science
language:en
Short-container-title:Protein Science

Author:

Allison Timothy M.¹,Degiacomi Matteo T.²,Marklund Erik G.³,Jovine Luca⁴,Elofsson Arne⁵,Benesch Justin L. P.⁶,Landreh Michael⁷^ORCID

Affiliation:

1. Biomolecular Interaction Centre, School of Physical and Chemical Sciences University of Canterbury Christchurch New Zealand

2. Department of Physics Durham University Durham UK

3. Department of Chemistry – BMC Uppsala University Uppsala Sweden

4. Department of Biosciences and Nutrition Karolinska Institutet Huddinge Sweden

5. Science for Life Laboratory and Department of Biochemistry and Biophysics Stockholm University Solna Sweden

6. Department of Chemistry University of Oxford Oxford UK

7. Department of Microbiology, Tumor and Cell Biology Karolinska Institutet – Biomedicum Stockholm Sweden

Funder

Cancerfonden

Vetenskapsrådet

Publisher

Wiley

Subject

Molecular Biology,Biochemistry

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/pro.4333

Reference25 articles.

1. Accurate prediction of protein structures and interactions using a three-track neural network

2. Highly accurate protein structure prediction for the human proteome

3. Highly accurate protein structure prediction with AlphaFold

4. NMR hawk‐eyed view of AlphaFold2 structures

5. Improved prediction of protein-protein interactions using AlphaFold2

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4. AI-Assisted Methods for Protein Structure Prediction and Analysis;Microorganisms for Sustainability;2024

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