Author

P. Afonine

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Biochemistry· 4 Biophysics· 2

Signature Assays, Organisms & Methods

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Assay:cryo-EM· 4 Approach:deep learning· 4 Research Focus:protein structure prediction· 3 Approach:statistical model· 3 Research Focus:benchmarking· 2 Assay:protein structure· 2 Approach:benchmark study· 1 Approach:contrastive learning· 1

Frequent Co-Authors

P. D. Adams· 4 shared T. C. Terwilliger· 4 shared J. S. Richardson· 3 shared R. J. Read· 3 shared B. K. Poon· 2 shared O. V. Sobolev· 2 shared A. Gobet· 1 shared A. J. McCoy· 1 shared

Activity by Year

2018-2022 · peak 3/yr

Co-Author Collaboration Network

10 top collaborators · 25 mutual co-author links

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4 shared papersBiochemistry

P. D. Adams

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Author profile →

6 papers

Recent·Most cited

Conformational space exploration of cryo-EM structures by variability refinement

P. Afonine, A. Gobet, L. Moissonnier, B. Poon, v. Chaptal

This paper introduces a tool to refine ensembles of structures into maps from cryo-EM variability analysis, enabling identification of variable and static structural elements.

bioRxiv · Dec 23, 2022Biophysics

AlphaFold predictions are valuable hypotheses, and accelerate but do not replace experimental structure determination

T. C. Terwilliger, D. L. Leibschner, T. Croll, C. J. Williams, A. J. McCoy, B. K. Poon, P. Afonine, R. D. Oeffner, J. S. Richardson, R. J. Read, P. D. Adams

The paper evaluates high-confidence AlphaFold predictions against experimental crystal structures, showing they are accurate but require experimental validation for detailed structural features.

bioRxiv · Nov 21, 2022Biochemistry

Improved AlphaFold modeling with implicit experimental information

T. C. Terwilliger, B. K. Poon, P. Afonine, C. J. Schlicksup, T. I. Croll, C. Millan-Nebot, J. S. Richardson, R. J. Read, P. D. Adams

The paper improves AlphaFold modeling by incorporating experimental density maps iteratively, resulting in more accurate protein structure predictions.

bioRxiv · Jan 7, 2022Biochemistry

Outcomes of the 2019 EMDataResource model challenge: validation of cryo-EM models at near-atomic resolution

C. L. Lawson, A. Kryshtafovych, P. D. Adams, P. Afonine, M. L. Baker, B. A. Barad, P. Bond, T. Burnley, R. Cao, J. Cheng, G. Chojnowski, K. Cowtan, K. A. Dill, F. DiMaio, D. Farrell, , Wan

The paper evaluates cryo-EM model quality using benchmark maps, showing high accuracy and reproducibility across 13 teams and recommending multiple metrics for model assessment.

bioRxiv · Jun 12, 2020Biochemistry

Density modification of cryo-EM maps

T. C. Terwilliger, O. V. Sobolev, P. Afonine, P. D. D. Adams, R. J. Read

The paper examines density modification for cryo-EM maps and presents a procedure to incorporate model-based information while reducing model bias.

bioRxiv · May 13, 2020Biochemistry

Map segmentation, automated model-building and their application to the Cryo-EM Model Challenge

T. Terwilliger, P. D. Adams, P. Afonine, O. V. Sobolev

The paper applies a segmentation method to cryo-EM maps to generate automated models for the 2016 cryo-EM model challenge, achieving varying completeness and RMS distances.

bioRxiv · Jul 10, 2018Biophysics