Frank DiMaio

32.0k total citations · 22 hit papers
150 papers, 13.6k citations indexed

About

Frank DiMaio is a scholar working on Molecular Biology, Materials Chemistry and Structural Biology. According to data from OpenAlex, Frank DiMaio has authored 150 papers receiving a total of 13.6k indexed citations (citations by other indexed papers that have themselves been cited), including 114 papers in Molecular Biology, 58 papers in Materials Chemistry and 20 papers in Structural Biology. Recurrent topics in Frank DiMaio's work include Enzyme Structure and Function (54 papers), Protein Structure and Dynamics (50 papers) and RNA and protein synthesis mechanisms (40 papers). Frank DiMaio is often cited by papers focused on Enzyme Structure and Function (54 papers), Protein Structure and Dynamics (50 papers) and RNA and protein synthesis mechanisms (40 papers). Frank DiMaio collaborates with scholars based in United States, United Kingdom and France. Frank DiMaio's co-authors include David Baker, Ray Yu‐Ruei Wang, Yifan Song, David E. Kim, Hahnbeom Park, Michael D. Tyka, Yifan Cheng, David Veesler, James Thompson and Edward H. Egelman and has published in prestigious journals such as Nature, Science and Cell.

In The Last Decade

Frank DiMaio

147 papers receiving 13.4k citations

Hit Papers

5 papers align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

The Rosetta All-Atom Energy Function for Macromolecular Modeling and Design

2017 942 citations Rebecca F. Alford, Andrew Leaver‐Fay et al. Journal of Chemical Theory and Computation profile →
High-Resolution Comparative Modeling with RosettaCM

2013 813 citations Frank DiMaio, Ray Yu‐Ruei Wang et al. Structure profile →
EMRinger: side chain–directed model and map validation for 3D cryo-electron microscopy

2015 568 citations Benjamin A. Barad, Nathaniel Echols et al. Nature Methods profile →
Cryo-electron microscopy structure of a coronavirus spike glycoprotein trimer

2016 386 citations Frank DiMaio et al. profile →
Structure prediction for CASP8 with all‐atom refinement using Rosetta

2009 380 citations David E. Kim, Elizabeth H. Kellogg et al. Proteins Structure Function and Bioinformatics profile →
Simultaneous Optimization of Biomolecular Energy Functions on Features from Small Molecules and Macromolecules

2016 352 citations Hahnbeom Park, Philip Bradley et al. Journal of Chemical Theory and Computation profile →
De novo protein design by deep network hallucination

2021 334 citations Ivan Anishchenko, Samuel J. Pellock et al. profile →
Glycan shield and epitope masking of a coronavirus spike protein observed by cryo-electron microscopy

2016 306 citations Frank DiMaio et al. Nature Structural & Molecular Biology profile →
Crystal structure of a monomeric retroviral protease solved by protein folding game players

2011 301 citations Frank DiMaio, David Baker et al. Nature Structural & Molecular Biology profile →
Relaxation of backbone bond geometry improves protein energy landscape modeling

2013 288 citations Frank DiMaio, David Baker et al. profile →
Alternate States of Proteins Revealed by Detailed Energy Landscape Mapping

2010 275 citations Frank DiMaio, David Baker et al. profile →
Atomic-accuracy models from 4.5-Å cryo-electron microscopy data with density-guided iterative local refinement

2015 244 citations Frank DiMaio, Thomas C. Marlovits et al. Nature Methods profile →
De novo design of protein homo-oligomers with modular hydrogen-bond network–mediated specificity

2016 232 citations Scott E. Boyken, Zibo Chen et al. Science profile →
High thermodynamic stability of parametrically designed helical bundles

2014 211 citations Frank DiMaio, David Baker et al. Science profile →
Design of ordered two-dimensional arrays mediated by noncovalent protein-protein interfaces

2015 195 citations Frank DiMaio, David Baker et al. Science profile →
Structure of the Type VI Secretion System Contractile Sheath

2015 187 citations David Baker, Frank DiMaio et al. profile →
Accurate prediction of protein–nucleic acid complexes using RoseTTAFoldNA

2023 176 citations Minkyung Baek, Ivan Anishchenko et al. Nature Methods profile →
Improving de novo protein binder design with deep learning

2023 158 citations Nathaniel R. Bennett, Brian Coventry et al. Nature Communications profile →
Cryo-EM structure of the protein-conducting ERAD channel Hrd1 in complex with Hrd3

2017 143 citations Sergey Ovchinnikov, Frank DiMaio et al. profile →
Hallucinating symmetric protein assemblies

2022 113 citations Justas Dauparas, Minkyung Baek et al. Science profile →
An artificial intelligence accelerated virtual screening platform for drug discovery

2024 69 citations Guangfeng Zhou, Hahnbeom Park et al. Nature Communications profile →
De novo design of pH-responsive self-assembling helical protein filaments

2024 34 citations Hao Shen, Eric M. Lynch et al. Nature Nanotechnology profile →

Peers

Countries citing papers authored by Frank DiMaio

Since Specialization

Citations

This map shows the geographic impact of Frank DiMaio's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Frank DiMaio with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Frank DiMaio more than expected).

Fields of papers citing papers by Frank DiMaio

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Frank DiMaio. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Frank DiMaio. The network helps show where Frank DiMaio may publish in the future.

Co-authorship network of co-authors of Frank DiMaio

This figure shows the co-authorship network connecting the top 25 collaborators of Frank DiMaio. A scholar is included among the top collaborators of Frank DiMaio based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Frank DiMaio. Frank DiMaio is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

#	Work	Indexed citations
1	Modeling protein–small molecule conformational ensembles with PLACER 2025 ·Proceedings of the National Academy of Sciences ·Ivan Anishchenko, Yakov Kipnis, Indrek Kalvet, Guangfeng Zhou, Rohith Krishna, Samuel J. Pellock, Anna Lauko, Gyu Rie Lee, Linna An, Justas Dauparas, Frank DiMaio, David Baker	3
2	De novo design of pH-responsive self-assembling helical protein filaments breakdown → 2024 ·Nature Nanotechnology ·Hao Shen, Eric M. Lynch, (unknown), Joseph L. Watson, Justin Decarreau, Neville P. Bethel, (unknown), William Sheffler, Daniel P. Farrell, Frank DiMaio, Emmanuel Derivery, James J. De Yoreo, (unknown), David Baker	34
3	Residue-level error detection in cryoelectron microscopy models 2023 ·Structure ·Gabriella Reggiano, (unknown), Daniel P. Farrell, Thomas C. Marlovits, Frank DiMaio	6
4	Improving de novo protein binder design with deep learning breakdown → 2023 ·Nature Communications ·Nathaniel R. Bennett, Brian Coventry, Inna Goreshnik, Buwei Huang, Aza Allen, Dionne Vafeados, (unknown), Justas Dauparas, Minkyung Baek, Lance Stewart, Frank DiMaio, Steven De Munck, Savvas N. Savvides, David Baker	158
5	Structure of the phosphoinositide 3-kinase (PI3K) p110γ-p101 complex reveals molecular mechanism of GPCR activation 2021 ·Science Advances ·Manoj Kumar Rathinaswamy, Udit Dalwadi, Kaelin D. Fleming, Carson Adams, (unknown), Els Pardon, Minkyung Baek, Oscar Vadas, Frank DiMaio, Jan Steyaert, Scott D. Hansen, Calvin K. Yip, John E. Burke	32
6	BRCA1/BARD1 site-specific ubiquitylation of nucleosomal H2A is directed by BARD1 2021 ·Nature Structural & Molecular Biology ·(unknown), Anika L. Burrell, Daniel P. Farrell, Jianming Kang, Meiling Wang, Jesse M. Hansen, (unknown), Lisa M. Tuttle, Mikaela D. Stewart, Peter S. Brzović, Champak Chatterjee, Weixing Zhao, Frank DiMaio, Justin M. Kollman, Rachel E. Klevit	58
7	Structural basis for autophagy inhibition by the human Rubicon–Rab7 complex 2020 ·Proceedings of the National Academy of Sciences ·Hersh K. Bhargava, Keisuke Tabata, (unknown), Maho Hamasaki, Daniel P. Farrell, Ivan Anishchenko, Frank DiMaio, Young Jun Im, Tamotsu Yoshimori, James H. Hurley	23
8	Perturbing the energy landscape for improved packing during computational protein design 2020 ·Proteins Structure Function and Bioinformatics ·Jack B. Maguire, Hugh K. Haddox, Devin Strickland, Samer Halabiya, Brian Coventry, (unknown), (unknown), (unknown), David F. Thieker, Eric Klavins, Thomas Szyperski, Frank DiMaio, David Baker, Brian Kuhlman	87
9	Polymerization in the actin ATPase clan regulates hexokinase activity in yeast 2020 ·Science ·(unknown), Eric M. Lynch, Daniel P. Farrell, Annie Dosey, Frank DiMaio, Tom A. Williams, Justin M. Kollman, Andrew W. Murray, Ethan C. Garner	40
10	An enumerative algorithm for de novo design of proteins with diverse pocket structures 2020 ·Proceedings of the National Academy of Sciences ·Benjamin Basanta, Matthew J. Bick, Asim K. Bera, Christoffer Norn, Cameron M. Chow, Lauren Carter, Inna Goreshnik, Frank DiMaio, David Baker	53
11	Phase separation of Polo-like kinase 4 by autoactivation and clustering drives centriole biogenesis 2019 ·Nature Communications ·Jung‐Eun Park, Liang Zhang, Jeong Kyu Bang, Þorkell Andrésson, Frank DiMaio, Kyung S. Lee	54
12	Protein homology model refinement by large-scale energy optimization 2018 ·Proceedings of the National Academy of Sciences ·Hahnbeom Park, Sergey Ovchinnikov, David E. Kim, Frank DiMaio, David Baker	47
13	Near-atomic model of microtubule-tau interactions 2018 ·Science ·Elizabeth H. Kellogg, (unknown), Simon Poepsel, Kenneth H. Downing, Frank DiMaio, Eva Nogales	272
14	Cryo-EM structure of the bacterial actin AlfA reveals unique assembly and ATP-binding interactions and the absence of a conserved subdomain 2018 ·Proceedings of the National Academy of Sciences ·(unknown), Frank DiMaio, Shun Kai Yang, Jesse M. Hansen, Jessica Polka, R. Dyche Mullins, Justin M. Kollman	8
15	Accurate computational design of multipass transmembrane proteins 2018 ·Science ·Peilong Lu, Duyoung Min, Frank DiMaio, Kathy Y. Wei, Michael D. Vahey, Scott E. Boyken, Zibo Chen, Jorge A. Fallas, George Ueda, William Sheffler, Vikram Khipple Mulligan, Wenqing Xu, James U. Bowie, David Baker	137
16	The Rosetta All-Atom Energy Function for Macromolecular Modeling and Design breakdown → 2017 ·Journal of Chemical Theory and Computation ·Rebecca F. Alford, Andrew Leaver‐Fay, Jeliazko R. Jeliazkov, Matthew J. O’Meara, Frank DiMaio, Hahnbeom Park, Maxim V. Shapovalov, P. Douglas Renfrew, Vikram Khipple Mulligan, Kalli Kappel, Jason W. Labonte, Michael S. Pacella, Richard Bonneau, Philip Bradley, Roland L. Dunbrack, Rhiju Das, David Baker, Brian Kuhlman, Tanja Kortemme, Jeffrey J. Gray	942
17	Improved de novo structure prediction in CASP 11 by incorporating coevolution information into Rosetta 2015 ·Proteins Structure Function and Bioinformatics ·Sergey Ovchinnikov, David E. Kim, Ray Yu‐Ruei Wang, Yuan Liu, Frank DiMaio, David Baker	77
18	EMRinger: side chain–directed model and map validation for 3D cryo-electron microscopy breakdown → 2015 ·Nature Methods ·Benjamin A. Barad, Nathaniel Echols, Ray Yu‐Ruei Wang, Yifan Cheng, Frank DiMaio, Paul D. Adams, James S. Fraser	568
19	A probabilistic approach to protein backbone tracing in electron density maps 2006 ·Bioinformatics ·Frank DiMaio, Jude Shavlik, G.N. Phillips	19
20	Pictorial Structures for Molecular Modeling: Interpreting Density Maps 2004 ·Neural Information Processing Systems ·Frank DiMaio, G.N. Phillips, Jude Shavlik	2

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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