Suhkmann Kim

3.7k total citations
150 papers, 2.8k citations indexed

About

Suhkmann Kim is a scholar working on Molecular Biology, Immunology and Aquatic Science. According to data from OpenAlex, Suhkmann Kim has authored 150 papers receiving a total of 2.8k indexed citations (citations by other indexed papers that have themselves been cited), including 92 papers in Molecular Biology, 27 papers in Immunology and 15 papers in Aquatic Science. Recurrent topics in Suhkmann Kim's work include Metabolomics and Mass Spectrometry Studies (38 papers), Aquaculture disease management and microbiota (21 papers) and Genomics, phytochemicals, and oxidative stress (9 papers). Suhkmann Kim is often cited by papers focused on Metabolomics and Mass Spectrometry Studies (38 papers), Aquaculture disease management and microbiota (21 papers) and Genomics, phytochemicals, and oxidative stress (9 papers). Suhkmann Kim collaborates with scholars based in South Korea, United States and United Kingdom. Suhkmann Kim's co-authors include Dahye Yoon, Heui‐Soo Kim, Yuan Chen, Hee‐Jae Cha, Yung Hyun Choi, Michael H. Tatham, Ronald T. Hay, Gi‐Young Kim, Cheol Park and Kyu‐Bong Kim and has published in prestigious journals such as Journal of Biological Chemistry, Angewandte Chemie International Edition and SHILAP Revista de lepidopterología.

In The Last Decade

Suhkmann Kim

146 papers receiving 2.8k citations

Peers

Suhkmann Kim
Comparison fields: 5 of 137
  • Molecular Biology 1.5k
  • Immunology 273
  • Materials Chemistry 270
  • Electrical and Electronic Engineering 206
  • Health, Toxicology and Mutagenesis 196
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Citations per field, relative to Suhkmann Kim
Suhkmann Kim · 1×
Citations per year, relative to Suhkmann Kim
Suhkmann Kim · 1×

Countries citing papers authored by Suhkmann Kim

Since Specialization
Citations

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

Fields of papers citing papers by Suhkmann Kim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Suhkmann Kim

This figure shows the co-authorship network connecting the top 25 collaborators of Suhkmann Kim. A scholar is included among the top collaborators of Suhkmann Kim 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 Suhkmann Kim. Suhkmann Kim 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
# Work Indexed citations
1 0
2 3
3 14
4 5
5 4
6 7
7 3
8
NMR-based Metabolomic Responses of Zebrafish (Danio Rerio) by Fipronil Exposure
1
9 15
10 7
11 17
12 15
13 15
14 19
15 30
16 25
17 77
18 19
19 13
20
Environment-dependent one-body score function for proteins by perceptron learning and protein threading
2

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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