Dae-Ook Kang

456 citations
37 papers · 363 · h-index 11

Impact in

Papers in

    • Microbial Metabolic Engineering and Bioproduction 4
    • Natural product bioactivities and synthesis 3
    • Glycosylation and Glycoproteins Research 2
    • Enzyme Production and Characterization 8

Dae-Ook Kang

33 papers receiving 335 citations

Peers

Dae-Ook Kang
Comparison fields: 5 of 63
  • Biotechnology 58
  • Organic Chemistry 111
  • Immunology 70
  • Molecular Biology 233
  • Biochemistry 15
Replace Ken Kitajima with:
Ken Kitajima Japan
Dong Ho Hong South Korea
K. U. Bindseil Germany
Valentin Prisecaru United States
Kiyofumi Wanibuchi Japan
Yoshikiyo Sakakibara Japan
Xiaoyu Tao China
Sheng-Ying Qin China
Woo‐Young Yang South Korea
Prashanth Srinivasan Canada
Dae-Ook Kang relative to Ken Kitajima Japan Ken Kitajima's profile →
Citations per field
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Ken Kitajima · 1×
Citations per year

Countries citing papers authored by Dae-Ook Kang

Since Specialization
Citations

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

Fields of papers citing papers by Dae-Ook Kang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Dae-Ook Kang. 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 Dae-Ook Kang. The network helps show where Dae-Ook Kang may publish in the future.

Co-authors

The 25 scholars most cited alongside Dae-Ook Kang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Dae-Ook Kang Line = papers co-authored together Dae-Ook Kang links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 37 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200673
2 199237
3 201327
4 201524
5 201421
6 201320
7 200319
8 200817
9 199817
10 200213
11 201110
12 201210
13
Characteristics of bacteriocin produced by Lactococcus lactis ET45 isolated from Kimchi
20119
14 20009
15 20007
16 20156
17 20156
18 19945
19 19964
20 20124

About Dae-Ook Kang

Dae-Ook Kang is a scholar working on Molecular Biology, Biotechnology, Biomedical Engineering, Plant Science and Organic Chemistry, having authored 37 papers that have together received 363 indexed citations. Recurring topics across this work include Enzyme Production and Characterization (8 papers), Biofuel production and bioconversion (5 papers), Microbial Metabolic Engineering and Bioproduction (4 papers), Probiotics and Fermented Foods (4 papers), Natural product bioactivities and synthesis (3 papers), Microbial Metabolites in Food Biotechnology (3 papers), Glycosylation and Glycoproteins Research (2 papers) and Galectins and Cancer Biology (2 papers). The work is most often cited by research in Biotechnology (58 citations), Organic Chemistry (111 citations), Immunology (70 citations), Molecular Biology (233 citations) and Biochemistry (15 citations). Dae-Ook Kang has collaborated with scholars based in South Korea, United States and Japan. Frequent co-authors include Dona C. Love, John A. Hanover, Eun Ju Kim, Jong Seog Ahn, Si Myung Byun, Bo Yeon Kim, Won Keun Oh, Nack‐Shick Choi, Soon‐Cheol Ahn and Chang‐Su Park. Their work appears in journals such as IUBMB Life, Planta Medica, The Journal of Microbiology, Biotechnology Letters and Carbohydrate Research.

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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