Hee‐Don Chae

1.3k citations
40 papers · 1.0k · h-index 18

Impact in

Papers in

Hee‐Don Chae

37 papers receiving 1.0k citations

Peers

Hee‐Don Chae
Comparison fields: 5 of 92
  • Geriatrics and Gerontology 79
  • Endocrine and Autonomic Systems 90
  • Aging 18
  • Molecular Biology 659
  • Physiology 40
Replace Laura R. Pearce with:
Laura R. Pearce United Kingdom
Judith Reilly United States
Greg M. Findlay United Kingdom
Miranda van Triest Netherlands
Luisa Di Stefano United States
Juan Manuel García‐Martínez Spain
Jaclyn S. Long United Kingdom
Xiangbin Zhang United States
Deanna M. Stevens United States
Makoto Katayama Japan
Hee‐Don Chae relative to Laura R. Pearce United Kingdom Laura R. Pearce's profile →
Citations per field
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Citations per year

Countries citing papers authored by Hee‐Don Chae

Since Specialization
Citations

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

Fields of papers citing papers by Hee‐Don Chae

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 40 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Constitutive activation of cyclin B1-associated cdc2 kinase overrides p53-mediated G2-M arrest.
200095
2 200691
3 201082
4 201075
5 200369
6 200568
7 200768
8 200458
9 201342
10 200437
11 201635
12 201032
13 199929
14 200125
15 199925
16 201722
17 201119
18 199617
19 201917
20 202016

About Hee‐Don Chae

Hee‐Don Chae is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience, Hematology, Oncology and Immunology, having authored 40 papers that have together received 1.0k indexed citations. Recurring topics across this work include Acute Myeloid Leukemia Research (6 papers), Receptor Mechanisms and Signaling (6 papers), RNA Interference and Gene Delivery (6 papers), Protein Kinase Regulation and GTPase Signaling (5 papers), Cancer-related Molecular Pathways (4 papers), RNA modifications and cancer (4 papers), Protein Degradation and Inhibitors (3 papers) and Sirtuins and Resveratrol in Medicine (3 papers). The work is most often cited by research in Geriatrics and Gerontology (79 citations), Endocrine and Autonomic Systems (90 citations), Aging (18 citations), Molecular Biology (659 citations) and Physiology (40 citations). Hee‐Don Chae has collaborated with scholars based in United States, South Korea and Japan. Frequent co-authors include Hal E. Broxmeyer, Deug Y. Shin, Kyong‐Tai Kim, David A. Williams, Yi Gu, Jeanho Yun, Jamie E. Siefring, Yung‐Jue Bang, David A. Hildeman and Jong‐So Kim. Their work appears in journals such as Blood, Journal of Biological Chemistry, Journal of Neurochemistry, Oncotarget and British Journal of Pharmacology.

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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