Dokyun Na

5.0k total citations · 3 hit papers
84 papers, 3.6k citations indexed

About

Dokyun Na is a scholar working on Molecular Biology, Genetics and Computational Theory and Mathematics. According to data from OpenAlex, Dokyun Na has authored 84 papers receiving a total of 3.6k indexed citations (citations by other indexed papers that have themselves been cited), including 63 papers in Molecular Biology, 15 papers in Genetics and 14 papers in Computational Theory and Mathematics. Recurrent topics in Dokyun Na's work include Computational Drug Discovery Methods (13 papers), RNA and protein synthesis mechanisms (12 papers) and CRISPR and Genetic Engineering (11 papers). Dokyun Na is often cited by papers focused on Computational Drug Discovery Methods (13 papers), RNA and protein synthesis mechanisms (12 papers) and CRISPR and Genetic Engineering (11 papers). Dokyun Na collaborates with scholars based in South Korea, Canada and Pakistan. Dokyun Na's co-authors include Sang Yup Lee, Seung Min Yoo, Bilal Shaker, Doheon Lee, Jingyu Lee, Jong Myoung Park, Sol Choi, Jeong Wook Lee, Joungmin Lee and Hannah Chung and has published in prestigious journals such as Nucleic Acids Research, Nature Biotechnology and Bioinformatics.

In The Last Decade

Dokyun Na

80 papers receiving 3.6k citations

Hit Papers

Systems metabolic engineering of microorganisms for natur... 2012 2026 2016 2021 2012 2013 2021 100 200 300 400 500
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.

  1. Systems metabolic engineering of microorganisms for natural and non-natural chemicals
    2012 553 citations Jeong Wook Lee, Dokyun Na et al. Nature Chemical Biology profile →
  2. Metabolic engineering of Escherichia coli using synthetic small regulatory RNAs
    2013 505 citations Dokyun Na, Sang Yup Lee et al. profile →
  3. In silico methods and tools for drug discovery
    2021 352 citations Bilal Shaker, Sajjad Ahmad et al. Computers in Biology and Medicine profile →

Peers

Dokyun Na
Ziding Zhang China
Diogo M. Camacho United States
Hao Liu China
Dong‐Yup Lee Singapore
Jan Brezovský Czechia
Xiujun Zhang China
Yang Cao China
Hojung Nam South Korea
Daniel R. Hyduke United States
Ziding Zhang China
Dokyun Na
Citations per year, relative to Dokyun Na Dokyun Na (= 1×) peers Ziding Zhang

Countries citing papers authored by Dokyun Na

Since Specialization
Citations

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

Fields of papers citing papers by Dokyun Na

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dokyun Na

This figure shows the co-authorship network connecting the top 25 collaborators of Dokyun Na. A scholar is included among the top collaborators of Dokyun Na 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 Dokyun Na. Dokyun Na 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.
Na, Dokyun, et al.. (2025). Challenging AlphaFold in predicting proteins with large-scale allosteric transitions. Communications Chemistry. 8(1). 378–378.
2.
Kim, Ji Hun, Bilal Shaker, Ara Ko, et al.. (2025). Precision medicine approach for in vitro modeling and computational screening of anti-epileptic drugs in pediatric epilepsy patients with SCN2A (R1629L) mutation. Computers in Biology and Medicine. 191. 110100–110100.
3.
Lee, Kangseok, et al.. (2025). Genetic “expiry-date” circuits control lifespan of synthetic scavenger bacteria for safe bioremediation. Nucleic Acids Research. 53(14). 2 indexed citations
4.
Na, Dokyun, et al.. (2025). Untranslated region engineering strategies for gene overexpression, fine-tuning, and dynamic regulation. The Journal of Microbiology. 63(3). e2501033–e2501033.
5.
Bui, Jennifer M., et al.. (2024). Widespread alteration of protein autoinhibition in human cancers. Cell Systems. 15(3). 246–263.e7. 1 indexed citations
6.
Ren, Jun, et al.. (2023). Evaluation of Various Escherichia coli Strains for Enhanced Lycopene Production. Journal of Microbiology and Biotechnology. 33(7). 973–979. 4 indexed citations
7.
Na, Dokyun, et al.. (2022). A machine learning model for classifying G-protein-coupled receptors as agonists or antagonists. BMC Bioinformatics. 23(S9). 346–346. 16 indexed citations
8.
Bae, Yeonju, et al.. (2021). NFIB induces functional astrocytes from human pluripotent stem cell‐derived neural precursor cells mimicking in vivo astrogliogenesis. Journal of Cellular Physiology. 236(11). 7625–7641. 15 indexed citations
9.
Lee, Hyang‐Mi, et al.. (2021). Optimized expression of Hfq protein increases Escherichia coli growth. Journal of Biological Engineering. 15(1). 7–7. 9 indexed citations
10.
Lee, Sung‐Gwon, Dokyun Na, & Chungoo Park. (2021). Comparability of reference-based and reference-free transcriptome analysis approaches at the gene expression level. BMC Bioinformatics. 22(S11). 310–310. 14 indexed citations
11.
Shaker, Bilal, et al.. (2021). In silico methods and tools for drug discovery. Computers in Biology and Medicine. 137. 104851–104851. 352 indexed citations breakdown →
12.
13.
Yeon, Ju Hun, Siwoo Cho, Kimin Kim, et al.. (2018). Cancer-derived exosomes trigger endothelial to mesenchymal transition followed by the induction of cancer-associated fibroblasts. Acta Biomaterialia. 76. 146–153. 139 indexed citations
14.
Cho, Hyeyoung, et al.. (2016). Meta-analysis method for discovering reliable biomarkers by integrating statistical and biological approaches: An application to liver toxicity. Biochemical and Biophysical Research Communications. 471(2). 274–281. 10 indexed citations
15.
Lim, Dong‐Jin, et al.. (2016). Microengineered platforms for co-cultured mesenchymal stem cells towards vascularized bone tissue engineering. Tissue Engineering and Regenerative Medicine. 13(5). 465–474. 18 indexed citations
16.
Na, Dokyun, Mushfiqur Rouf, Cahir J. O’Kane, David C. Rubinsztein, & Jörg Gsponer. (2013). NeuroGeM, a knowledgebase of genetic modifiers in neurodegenerative diseases. BMC Medical Genomics. 6(1). 52–52. 21 indexed citations
17.
Lee, Jeong Wook, Dokyun Na, Jong Myoung Park, et al.. (2012). Systems metabolic engineering of microorganisms for natural and non-natural chemicals. Nature Chemical Biology. 8(6). 536–546. 553 indexed citations breakdown →
18.
Yeon, Ju Hun, Dokyun Na, Kyungsun Choi, et al.. (2012). Reliable permeability assay system in a microfluidic device mimicking cerebral vasculatures. Biomedical Microdevices. 14(6). 1141–1148. 103 indexed citations
19.
Na, Dokyun, Sunjae Lee, Gwan‐Su Yi, & Doheon Lee. (2011). Synthetic inter-species cooperation of host and virus for targeted genetic evolution. Journal of Biotechnology. 153(1-2). 35–41. 4 indexed citations
20.
Na, Dokyun, et al.. (2006). Fuzzy continuous petri net-based approach for modeling immune systems. Lecture notes in computer science. 3931. 278–285. 3 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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