Jun‐Mo Kim

2.5k citations
160 papers · 1.8k · h-index 23

Impact in

Papers in

    • Meat and Animal Product Quality 21
    • Animal Nutrition and Physiology 20
    • Animal Virus Infections Studies 10
    • Genetic and phenotypic traits in livestock 24
    • Genetic Mapping and Diversity in Plants and Animals 11

Jun‐Mo Kim

152 papers receiving 1.8k citations

Peers

Jun‐Mo Kim
Comparison fields: 5 of 162
  • Animal Science and Zoology 356
  • Endocrinology 80
  • Molecular Medicine 63
  • Cancer Research 163
  • Environmental Engineering 173
Replace Qishan Wang with:
Qishan Wang China
María Cruz Rodríguez Spain
Chao Ye China
Rui Guo China
María Teresa Tejedor Spain
Dongwan Don Kang United States
Bong‐Joo Lee South Korea
Françoise I. Bussière France
Chang Ho Yu China
Fréderic Escudié France
Jun‐Mo Kim relative to Qishan Wang China Qishan Wang's profile →
Citations per field
00.5×2×3.1×
Qishan Wang · 1×
Citations per year

Countries citing papers authored by Jun‐Mo Kim

Since Specialization
Citations

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

Fields of papers citing papers by Jun‐Mo Kim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 160 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2015104
2 199787
3 199748
4 200741
5 201838
6 201938
7 201833
8 199932
9 202130
10 201930
11 201829
12 201229
13 201929
14 201627
15 202227
16 202226
17 201126
18 202426
19 200526
20 201926

About Jun‐Mo Kim

Jun‐Mo Kim is a scholar working on Animal Science and Zoology, Genetics, Cancer Research, Environmental Engineering and Small Animals, having authored 160 papers that have together received 1.8k indexed citations. Recurring topics across this work include Genetic and phenotypic traits in livestock (24 papers), Meat and Animal Product Quality (21 papers), Animal Nutrition and Physiology (20 papers), Cancer-related molecular mechanisms research (15 papers), Genetic Mapping and Diversity in Plants and Animals (11 papers), Animal Virus Infections Studies (10 papers), Groundwater flow and contamination studies (9 papers) and Effects and risks of endocrine disrupting chemicals (8 papers). The work is most often cited by research in Animal Science and Zoology (356 citations), Endocrinology (80 citations), Molecular Medicine (63 citations), Cancer Research (163 citations) and Environmental Engineering (173 citations). Jun‐Mo Kim has collaborated with scholars based in South Korea, United States and Netherlands. Frequent co-authors include Richard R. Parizek, Rajesh Kumar Pathak, Do‐Young Kim, Youn‐Chul Ryu, Jong‐Eun Park, Dajeong Lim, Seung-Hoon Lee, Kyung‐Tai Lee, Dong Yong Kil and Derek Elsworth. Their work appears in journals such as Animals, Journal of Animal Science and Technology, Meat Science, Journal of Animal Science and Poultry Science.

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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