Gap‐Don Kim

2.0k citations
63 papers · 1.6k · 1 hit paper · h-index 21

Impact in

Papers in

Gap‐Don Kim

60 papers receiving 1.5k citations

Gap‐Don Kim's Hit Papers

Review of the Current Research on Fetal Bovine Serum and the Development of Cultured Meat 2022 · 142 citations
1420+1+2Years since publication4080120

Peers

Gap‐Don Kim
Comparison fields: 5 of 99
  • Animal Science and Zoology 982
  • Food Science 293
  • Insect Science 141
  • Cell Biology 139
  • Molecular Biology 571
Replace Jin‐Yeon Jeong with:
Jin‐Yeon Jeong South Korea
M. Wicke Germany
Mahesh N. Nair United States
Francesca Soglia Italy
B.C. Kim South Korea
Jeehwan Choe South Korea
Brian Bowker United States
G. G. Mafi United States
C. Gariépy Canada
Xiaojing Tian China
Gap‐Don Kim relative to Jin‐Yeon Jeong South Korea Jin‐Yeon Jeong's profile →
Citations per field
00.5×3.0×
Jin‐Yeon Jeong · 1×
Citations per year

Countries citing papers authored by Gap‐Don Kim

Since Specialization
Citations

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

Fields of papers citing papers by Gap‐Don Kim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Gap‐Don 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 Gap‐Don Kim. The network helps show where Gap‐Don Kim may publish in the future.

Co-authors

The 25 scholars most cited alongside Gap‐Don Kim, 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 Gap‐Don Kim Line = papers co-authored together Gap‐Don Kim links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 63 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2010228
2
Review of the Current Research on Fetal Bovine Serum and the Development of Cultured Meat
Hit paper breakdown →
2022142
3 2013121
4 202074
5 202274
6 202256
7 201648
8 201345
9 201144
10 201444
11 202339
12 201639
13 201936
14 201535
15 202034
16 201732
17 202126
18 201825
19 201124
20 201323

About Gap‐Don Kim

Gap‐Don Kim is a scholar working on Animal Science and Zoology, Molecular Biology, Food Science, Nutrition and Dietetics and Small Animals, having authored 63 papers that have together received 1.6k indexed citations. Recurring topics across this work include Meat and Animal Product Quality (56 papers), Animal Nutrition and Physiology (19 papers), Food Quality and Safety Studies (11 papers), Muscle Physiology and Disorders (9 papers), Protein Hydrolysis and Bioactive Peptides (8 papers), Nutrition, Health and Food Behavior (7 papers), Muscle metabolism and nutrition (5 papers) and Insect Utilization and Effects (5 papers). The work is most often cited by research in Animal Science and Zoology (982 citations), Food Science (293 citations), Insect Science (141 citations), Cell Biology (139 citations) and Molecular Biology (571 citations). Gap‐Don Kim has collaborated with scholars based in South Korea, United States and Puerto Rico. Frequent co-authors include Jin‐Yeon Jeong, Seon-Tea Joo, Sun Jin Hur, Han‐Sul Yang, Jungseok Choi, Young-Hwa Hwang, Sang-Keun Jin, Eun‐Young Jung, Sumin Song and Hyun‐Tae Lim. Their work appears in journals such as Food Science of Animal Resources, Meat Science, LWT, Journal of Animal Science and Technology and Food Chemistry.

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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