Tae‐Eun Kim

2.5k citations
83 papers · 1.6k indexed · h-index 22
Topics
Diabetes Treatment and Management (11 papers)Drug Transport and Resistance Mechanisms (9 papers)Pharmacological Effects and Toxicity Studies (8 papers)

In The Last Decade

Tae‐Eun Kim

76 papers receiving 1.5k citations

Peers

Tae‐Eun Kim
Comparison fields: 5 of 136
  • Computer Networks and Communications 517
  • Electrical and Electronic Engineering 301
  • Molecular Biology 220
  • Oncology 212
  • Endocrinology, Diabetes and Metabolism 167
Replace Philip T. Sager with:
Philip T. Sager United States
Takahiko Aoyama Japan
Fugang Wang China
Toshio Wakabayashi Japan
Xuehua Jiang China
Sundararaman Swaminathan United States
Luca Rinaldi Italy
Kenji Tsuchida Japan
Chang-Yu Chen Taiwan
Martin Kaufmann Canada
Tae‐Eun Kim relative to Philip T. Sager United States Philip T. Sager's profile →
Citations per field
00.5×9.1×
Philip T. Sager · 1×
Citations per year

Countries citing papers authored by Tae‐Eun Kim

Since Specialization
Citations

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

Fields of papers citing papers by Tae‐Eun Kim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tae‐Eun Kim

This figure shows the co-authorship network connecting the top 25 collaborators of Tae‐Eun Kim. A scholar is included among the top collaborators of Tae‐Eun 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 Tae‐Eun Kim. Tae‐Eun 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
#WorkIndexed citations
1 0
2 0
3 1
4 2
5 13
6 26
7 8
8 20
9 11
10 66
11 17
12 2
13 6
14 11
15 41
16
Projecting Social Expenditure and Total Tax Burden in Korea-A Study on Forecasting Social Expenditure for OECD Countries and Corresponding Total Tax Revenue for Korea
0
17 7
18 5
19 6
20 13

About Tae‐Eun Kim

Tae‐Eun Kim is a scholar working on Endocrinology, Diabetes and Metabolism, Pharmacology and Pharmacology, having authored 83 papers that have together received 1.6k indexed citations. Recurring topics across this work include Diabetes Treatment and Management (11 papers), Drug Transport and Resistance Mechanisms (9 papers) and Pharmacological Effects and Toxicity Studies (8 papers). The work is most often cited by research in Computer Networks and Communications (517 citations), Pharmacology (127 citations) and Endocrinology, Diabetes and Metabolism (167 citations). Tae‐Eun Kim has collaborated with scholars based in South Korea, United States and Puerto Rico. Frequent co-authors include V. Bharghavan, Thyaga Nandagopal, Xia Gao, Joo‐Youn Cho, Kyung‐Sang Yu, In‐Jin Jang, Seo Hyun Yoon, Sang-Goo Shin, SoJeong Yi and Kyoung Soo Lim. Their work appears in journals such as Journal of Hazardous Materials, Brain Research and Human Molecular Genetics.

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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