Howook Hwang

3.7k total citations · 1 hit paper
18 papers, 2.5k citations indexed

About

Howook Hwang is a scholar working on Molecular Biology, Computational Theory and Mathematics and Materials Chemistry. According to data from OpenAlex, Howook Hwang has authored 18 papers receiving a total of 2.5k indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Molecular Biology, 9 papers in Computational Theory and Mathematics and 6 papers in Materials Chemistry. Recurrent topics in Howook Hwang's work include Protein Structure and Dynamics (17 papers), Computational Drug Discovery Methods (9 papers) and Enzyme Structure and Function (6 papers). Howook Hwang is often cited by papers focused on Protein Structure and Dynamics (17 papers), Computational Drug Discovery Methods (9 papers) and Enzyme Structure and Function (6 papers). Howook Hwang collaborates with scholars based in United States, France and Netherlands. Howook Hwang's co-authors include Zhiping Weng, Thom Vreven, Brian G. Pierce, Kevin Wiehe, Bong‐Hyun Kim, Joël Janin, Julian Mintseris, Panagiotis L. Kastritis, Paul A. Bates and Alexandre M. J. J. Bonvin and has published in prestigious journals such as Cell, Proceedings of the National Academy of Sciences and Blood.

In The Last Decade

Howook Hwang

18 papers receiving 2.5k citations

Hit Papers

ZDOCK server: interactive docking prediction of protein–p... 2014 2026 2018 2022 2014 400 800 1.2k

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Howook Hwang United States 13 2.1k 622 533 262 209 18 2.5k
Stephen R. Comeau United States 11 2.1k 1.0× 441 0.7× 433 0.8× 371 1.4× 317 1.5× 19 2.7k
Ryan Brenke United States 11 1.5k 0.7× 536 0.9× 333 0.6× 266 1.0× 183 0.9× 13 1.9k
Björn Wallner Sweden 31 3.0k 1.5× 477 0.8× 884 1.7× 168 0.6× 172 0.8× 74 3.6k
Matthew J. O’Meara United States 17 2.0k 1.0× 656 1.1× 547 1.0× 257 1.0× 107 0.5× 29 2.7k
Ivan Anishchenko United States 19 2.5k 1.2× 372 0.6× 598 1.1× 196 0.7× 120 0.6× 37 3.1k
Brian Jiménez‐García Spain 19 1.6k 0.7× 389 0.6× 302 0.6× 290 1.1× 157 0.8× 30 1.9k
Julian Mintseris United States 24 2.9k 1.4× 640 1.0× 762 1.4× 168 0.6× 172 0.8× 35 3.3k
Andrew A. Bogan United States 6 1.9k 0.9× 379 0.6× 432 0.8× 328 1.3× 157 0.8× 8 2.3k
Adrien S. J. Melquiond Netherlands 19 2.4k 1.2× 403 0.6× 381 0.7× 304 1.2× 302 1.4× 23 3.2k
Zhenling Peng China 29 3.5k 1.7× 446 0.7× 725 1.4× 165 0.6× 148 0.7× 60 4.1k

Countries citing papers authored by Howook Hwang

Since Specialization
Citations

This map shows the geographic impact of Howook Hwang'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 Howook Hwang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Howook Hwang more than expected).

Fields of papers citing papers by Howook Hwang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Howook Hwang. 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 Howook Hwang. The network helps show where Howook Hwang may publish in the future.

Co-authorship network of co-authors of Howook Hwang

This figure shows the co-authorship network connecting the top 25 collaborators of Howook Hwang. A scholar is included among the top collaborators of Howook Hwang 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 Howook Hwang. Howook Hwang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

18 of 18 papers shown
1.
Miller, Edward B., Howook Hwang, Mee Shelley, et al.. (2024). Enabling structure-based drug discovery utilizing predicted models. Cell. 187(3). 521–525. 10 indexed citations
2.
Trudeau, Stephen J., Howook Hwang, Deepika Mathur, et al.. (2023). PrePCI : A structure‐ and chemical similarity‐informed database of predicted protein compound interactions. Protein Science. 32(4). e4594–e4594. 8 indexed citations
3.
Liu, Yuxuan, Jole Fiorito, Elisa Calcagno, et al.. (2019). Strategy for Overcoming Crebbp and EP300 Mutations in Lymphoma: Development of First-in-Class HAT Activators. Blood. 134(Supplement_1). 4068–4068. 4 indexed citations
4.
Hwang, Howook, Fabian Dey, Donald Petrey, & Barry Honig. (2017). Structure-based prediction of ligand–protein interactions on a genome-wide scale. Proceedings of the National Academy of Sciences. 114(52). 13685–13690. 40 indexed citations
5.
Petrey, Donald, Lei Deng, José Ignacio Garzón, et al.. (2015). Template-based prediction of protein function. Current Opinion in Structural Biology. 32. 33–38. 33 indexed citations
6.
Hwang, Howook, Donald Petrey, & Barry Honig. (2015). A hybrid method for protein–protein interface prediction. Protein Science. 25(1). 159–165. 27 indexed citations
7.
Pierce, Brian G., Kevin Wiehe, Howook Hwang, et al.. (2014). ZDOCK server: interactive docking prediction of protein–protein complexes and symmetric multimers. Bioinformatics. 30(12). 1771–1773. 1276 indexed citations breakdown →
8.
Vreven, Thom, Howook Hwang, & Zhiping Weng. (2013). Exploring Angular Distance in Protein-Protein Docking Algorithms. PLoS ONE. 8(2). e56645–e56645. 10 indexed citations
9.
Hwang, Howook, Thom Vreven, & Zhiping Weng. (2013). Binding interface prediction by combining protein-protein docking results. Proteins Structure Function and Bioinformatics. 82(1). 57–66. 23 indexed citations
10.
Vreven, Thom, Brian G. Pierce, Howook Hwang, & Zhiping Weng. (2013). Performance of ZDOCK in CAPRI rounds 20–26. Proteins Structure Function and Bioinformatics. 81(12). 2175–2182. 21 indexed citations
11.
Vreven, Thom, Howook Hwang, Brian G. Pierce, & Zhiping Weng. (2012). Prediction of protein–protein binding free energies. Protein Science. 21(3). 396–404. 67 indexed citations
12.
Hwang, Howook, Thom Vreven, Troy W. Whitfield, Kevin Wiehe, & Zhiping Weng. (2011). A machine learning approach for the prediction of protein surface loop flexibility. Proteins Structure Function and Bioinformatics. 79(8). 2467–2474. 6 indexed citations
13.
Vreven, Thom, Howook Hwang, & Zhiping Weng. (2011). Integrating atom‐based and residue‐based scoring functions for protein–protein docking. Protein Science. 20(9). 1576–1586. 67 indexed citations
14.
Kastritis, Panagiotis L., Iain H. Moal, Howook Hwang, et al.. (2011). A structure‐based benchmark for protein–protein binding affinity. Protein Science. 20(3). 482–491. 234 indexed citations
15.
Hwang, Howook, Thom Vreven, Brian G. Pierce, Jui‐Hung Hung, & Zhiping Weng. (2010). Performance of ZDOCK and ZRANK in CAPRI rounds 13–19. Proteins Structure Function and Bioinformatics. 78(15). 3104–3110. 65 indexed citations
16.
Hwang, Howook, Thom Vreven, Joël Janin, & Zhiping Weng. (2010). Protein–protein docking benchmark version 4.0. Proteins Structure Function and Bioinformatics. 78(15). 3111–3114. 391 indexed citations
17.
Hwang, Howook, Brian G. Pierce, Julian Mintseris, Joël Janin, & Zhiping Weng. (2008). Protein–protein docking benchmark version 3.0. Proteins Structure Function and Bioinformatics. 73(3). 705–709. 206 indexed citations
18.
Wiehe, Kevin, Brian G. Pierce, Wei Tong, et al.. (2007). The performance of ZDOCK and ZRANK in rounds 6–11 of CAPRI. Proteins Structure Function and Bioinformatics. 69(4). 719–725. 59 indexed citations

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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