Yangsik Jeong

2.0k citations
29 papers · 1.6k indexed · 1 hit paper · h-index 18

Yangsik Jeong

28 papers receiving 1.6k citations

Hit Papers

Anatomical Profiling of Nuclear Receptor Expression Revea...8112006202620122019250500750

Peers

Yangsik Jeong
Comparison fields: 5 of 103
  • Cancer Research 265
  • Endocrinology, Diabetes and Metabolism 218
  • Molecular Biology 853
  • Applied Microbiology and Biotechnology 25
  • Genetics 325
Replace Bao Zhu with:
Bao Zhu United States
Nadia Bougarne Belgium
Iván P. Uray United States
Chi‐Wai Wong China
Lisong Teng China
Elżbieta Janda Italy
Phyllis H. Luckert United States
Shao‐Chih Chiu Taiwan
Damiano Cosimo Rigiracciolo Italy
Yangsik Jeong relative to Bao Zhu United States Bao Zhu's profile →
Citations per field
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Bao Zhu · 1×
Citations per year

Countries citing papers authored by Yangsik Jeong

Since Specialization
Citations

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

Fields of papers citing papers by Yangsik Jeong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20250
2 20246
3 202214
4 202025
5 202033
6 20206
7 201947
8 201812
9 201519
10 201528
11 201512
12 2014140
13 20149
14 20149
15 201225
16 201220
17 201057
18 200954
19 200872
20
Anatomical Profiling of Nuclear Receptor Expression Reveals a Hierarchical Transcriptional Networkbreakdown →
2006811

About Yangsik Jeong

Yangsik Jeong is a scholar working on Cancer Research, Applied Microbiology and Biotechnology and Biotechnology, having authored 29 papers that have together received 1.6k indexed citations. Recurring topics across this work include Cancer, Hypoxia, and Metabolism (8 papers), Peroxisome Proliferator-Activated Receptors (6 papers), Cancer, Lipids, and Metabolism (5 papers), Pluripotent Stem Cells Research (3 papers), Cancer Research and Treatments (3 papers), Estrogen and related hormone effects (3 papers), Cytokine Signaling Pathways and Interactions (3 papers) and Drug Transport and Resistance Mechanisms (2 papers). The work is most often cited by research in Cancer Research (265 citations), Endocrinology, Diabetes and Metabolism (218 citations) and Molecular Biology (853 citations). Yangsik Jeong has collaborated with scholars based in South Korea, United States and Japan. Frequent co-authors include David J. Mangelsdorf, Angie L. Bookout, Ruth T. Yu, Ronald M. Evans, Michael Downes, Kyu‐Sang Park, Yang Xie, Ki Woo Kim, Hiroyuki Miyachi and Makoto Makishima. Their work appears in journals such as Cell, PLoS ONE and Cancer Research.

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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