Woo Dae Jang

2.0k citations
23 papers · 1.4k indexed · 2 hit papers · h-index 13
Topics
Microbial Metabolic Engineering and Bioproduction (10 papers)Computational Drug Discovery Methods (7 papers)Enzyme Catalysis and Immobilization (5 papers)
Partner nations
South KoreaDenmarkCanada

In The Last Decade

Woo Dae Jang

22 papers receiving 1.4k citations

Hit Papers

A comprehensive metabolic map for production of bio-based...201920262021202320192019100200300400

Peers

Woo Dae Jang
Comparison fields: 5 of 103
  • Molecular Biology 922
  • Biomedical Engineering 484
  • Biomaterials 174
  • Biotechnology 137
  • Computational Theory and Mathematics 132
Replace Tuck Seng Wong with:
Tuck Seng Wong United Kingdom
Kang Lan Tee United Kingdom
Jae Sung Cho South Korea
Jiwen Zhang China
Jason T. Bouvier United States
Huang Ri-bo China
Neera Raghav India
Yinglu Cui China
Joo‐Hyun Seo South Korea
Woo Dae Jang relative to Tuck Seng Wong United Kingdom Tuck Seng Wong's profile →
Citations per field
00.5×10×
Tuck Seng Wong · 1×
Citations per year

Countries citing papers authored by Woo Dae Jang

Since Specialization
Citations

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

Fields of papers citing papers by Woo Dae Jang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Woo Dae Jang. 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 Woo Dae Jang. The network helps show where Woo Dae Jang may publish in the future.

Co-authorship network of co-authors of Woo Dae Jang

This figure shows the co-authorship network connecting the top 25 collaborators of Woo Dae Jang. A scholar is included among the top collaborators of Woo Dae Jang 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 Woo Dae Jang. Woo Dae Jang 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
#WorkIndexed citations
1 4
2 1
3 3
4 0
5 2
6 6
7 11
8 22
9 20
10 30
11 50
12 89
13 4
14 18
15 65
16
A comprehensive metabolic map for production of bio-based chemicalsbreakdown →
454
17
Systems Metabolic Engineering Strategies: Integrating Systems and Synthetic Biology with Metabolic Engineeringbreakdown →
396
18 53
19 11
20 12

About Woo Dae Jang

Woo Dae Jang is a scholar working on Computational Theory and Mathematics, Biomaterials and Molecular Biology, having authored 23 papers that have together received 1.4k indexed citations. Recurring topics across this work include Microbial Metabolic Engineering and Bioproduction (10 papers), Computational Drug Discovery Methods (7 papers) and Enzyme Catalysis and Immobilization (5 papers). The work is most often cited by research in Biotechnology (137 citations), Molecular Biology (922 citations) and Biomaterials (174 citations). Woo Dae Jang has collaborated with scholars based in South Korea, Denmark and Canada. Frequent co-authors include Sang Yup Lee, Jae Sung Cho, Dongsoo Yang, Hyun Uk Kim, Kyeong Rok Choi, Tong Un Chae, Dong In Kim, Jae Ho Shin, Yu‐Sin Jang and Je Woong Kim. Their work appears in journals such as Proceedings of the National Academy of Sciences, Journal of the American Chemical Society and Nature Communications.

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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