Doo Nam Kim

490 total citations
21 papers, 334 citations indexed

About

Doo Nam Kim is a scholar working on Molecular Biology, Computational Theory and Mathematics and Materials Chemistry. According to data from OpenAlex, Doo Nam Kim has authored 21 papers receiving a total of 334 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Molecular Biology, 4 papers in Computational Theory and Mathematics and 4 papers in Materials Chemistry. Recurrent topics in Doo Nam Kim's work include Enzyme Structure and Function (4 papers), Computational Drug Discovery Methods (3 papers) and Pharmacogenetics and Drug Metabolism (3 papers). Doo Nam Kim is often cited by papers focused on Enzyme Structure and Function (4 papers), Computational Drug Discovery Methods (3 papers) and Pharmacogenetics and Drug Metabolism (3 papers). Doo Nam Kim collaborates with scholars based in United States, South Korea and Austria. Doo Nam Kim's co-authors include Karissa Y. Sanbonmatsu, Kwang-Hwi Cho, Won‐Seok Oh, Kyoung Tai No, Scott P. Hennelly, Ivo L. Hofacker, Trushar R. Patel, Tyler Mrozowich, Timothy M. Jacobs and Brian Kuhlman and has published in prestigious journals such as Journal of Biological Chemistry, Nature Communications and Analytical Chemistry.

In The Last Decade

Doo Nam Kim

20 papers receiving 328 citations

Peers

Doo Nam Kim
Fiona Whelan United Kingdom
Brandon S. Zerbe United States
Thomas Evangelidis Greece
Dominik Toušěk Czechia
Elke Michalsky Germany
Sozanne R. Solmaz United States
Zeynep Kurkcuoglu Türkiye
Wen‐Ting Chu China
Jesse Woo United States
Zuzana Jandová Austria
Fiona Whelan United Kingdom
Doo Nam Kim
Citations per year, relative to Doo Nam Kim Doo Nam Kim (= 1×) peers Fiona Whelan

Countries citing papers authored by Doo Nam Kim

Since Specialization
Citations

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

Fields of papers citing papers by Doo Nam Kim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Doo Nam Kim. 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 Doo Nam Kim. The network helps show where Doo Nam Kim may publish in the future.

Co-authorship network of co-authors of Doo Nam Kim

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

All Works

20 of 20 papers shown
1.
Moinuddin, Syed, Clyde A. Smith, Robert Young, et al.. (2024). Dirigent isoflavene-forming PsPTS2: 3D structure, stereochemical, and kinetic characterization comparison with pterocarpan-forming PsPTS1 homolog in pea. Journal of Biological Chemistry. 300(3). 105647–105647. 2 indexed citations
2.
Kim, Doo Nam, Tianzhixi Yin, Tong Zhang, et al.. (2024). Artificial Intelligence Transforming Post-Translational Modification Research. Bioengineering. 12(1). 26–26. 6 indexed citations
3.
Li, Xiaolu, Marina Gritsenko, Matthew Gaffrey, et al.. (2024). Integrative Multi-PTM Proteomics Reveals Dynamic Global, Redox, Phosphorylation, and Acetylation Regulation in Cytokine-Treated Pancreatic Beta Cells. Molecular & Cellular Proteomics. 23(12). 100881–100881. 4 indexed citations
4.
Kim, Doo Nam, et al.. (2024). Leveraging Artificial Intelligence to Expedite Antibody Design and Enhance Antibody–Antigen Interactions. Bioengineering. 11(2). 185–185. 19 indexed citations
5.
Gosline, Sara J.C., Doo Nam Kim, Paritosh Pande, et al.. (2023). The Superfund Research Program Analytics Portal: linking environmental chemical exposure to biological phenotypes. Scientific Data. 10(1). 151–151. 3 indexed citations
6.
Kim, Doo Nam, et al.. (2022). Graph identification of proteins in tomograms (GRIP‐Tomo). Protein Science. 32(1). e4538–e4538. 1 indexed citations
7.
Kim, Doo Nam, et al.. (2022). A Comparative Multi-System Approach to Characterizing Bioactivity of Commonly Occurring Chemicals. International Journal of Environmental Research and Public Health. 19(7). 3829–3829. 3 indexed citations
8.
Novikova, Irina, Mowei Zhou, Doo Nam Kim, et al.. (2021). Tunable Heteroassembly of a Plant Pseudoenzyme–Enzyme Complex. ACS Chemical Biology. 16(11). 2315–2325. 11 indexed citations
9.
Kim, Doo Nam, Tyler Mrozowich, Scott P. Hennelly, et al.. (2020). Zinc-finger protein CNBP alters the 3-D structure of lncRNA Braveheart in solution. Nature Communications. 11(1). 148–148. 60 indexed citations
10.
Kim, Doo Nam, Dominik Gront, & Karissa Y. Sanbonmatsu. (2020). Practical Considerations for Atomistic Structure Modeling with Cryo-EM Maps. Journal of Chemical Information and Modeling. 60(5). 2436–2442. 8 indexed citations
11.
Lee, Sung Il, Doo Nam Kim, & Kyounghoon Lee. (2020). Characteristics on bycatch in Korean tuna purse seine fishery associated with FAD in the Indian Ocean by scientific observer programs. 56(4). 277–291. 2 indexed citations
12.
Kim, Doo Nam, Nigel W. Moriarty, Serdal Kırmızıaltın, et al.. (2019). Cryo_fit: Democratization of flexible fitting for cryo-EM. Journal of Structural Biology. 208(1). 1–6. 27 indexed citations
13.
Kim, Doo Nam & Karissa Y. Sanbonmatsu. (2017). Tools for the cryo-EM gold rush: going from the cryo-EM map to the atomistic model. Bioscience Reports. 37(6). 18 indexed citations
14.
Kim, Doo Nam, Timothy M. Jacobs, & Brian Kuhlman. (2015). Boosting protein stability with the computational design of β‐sheet surfaces. Protein Science. 25(3). 702–710. 23 indexed citations
15.
Redler, Rachel L., David Shirvanyants, Onur Dağliyan, et al.. (2014). Computational approaches to understanding protein aggregation in neurodegeneration. Journal of Molecular Cell Biology. 6(2). 104–115. 41 indexed citations
16.
17.
Kim, Kyung‐Kil, Young‐Ok Kim, Sooyeon Park, et al.. (2011). Shewanella upenei sp. nov., a lipolytic bacterium isolated from bensasi goatfish Upeneus bensasi. The Journal of Microbiology. 49(3). 381–386. 13 indexed citations
18.
Kim, Doo Nam, Kwang-Hwi Cho, Won‐Seok Oh, et al.. (2009). EaMEAD: Activation Energy Prediction of Cytochrome P450 Mediated Metabolism with Effective Atomic Descriptors. Journal of Chemical Information and Modeling. 49(7). 1643–1654. 19 indexed citations
19.
Oh, Won‐Seok, et al.. (2008). New Combined Model for the Prediction of Regioselectivity in Cytochrome P450/3A4 Mediated Metabolism. Journal of Chemical Information and Modeling. 48(3). 591–601. 36 indexed citations
20.
Kim, Nam Doo, Su Yeon Kim, Inhee Choi, et al.. (2008). Regioselectivity Prediction of CYP1A2-Mediated Phase I Metabolism. Journal of Chemical Information and Modeling. 48(5). 1074–1080. 31 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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