Hail Kim

80 papers receiving 3.9k citations

Hail Kim's Hit Papers

Psilocybin’s lasting action requires pyramidal cell types and 5-HT2A receptors 2025 · 35 citations
350+5+10Years since publication100200300400

Peers

Hail Kim
Comparison fields: 5 of 118
  • Biological Psychiatry 143
  • Endocrinology, Diabetes and Metabolism 697
  • Physiology 816
  • Endocrine and Autonomic Systems 205
  • Surgery 1.2k
Replace Gu Seob Roh with:
Gu Seob Roh South Korea
Naoko Yamauchi Japan
Hiroki Mizukami Japan
Motonobu Anai Japan
Carla Roberta de Oliveira Carvalho Brazil
Ângelo Rafael Carpinelli Brazil
Marc Uldry Switzerland
Éric Hajduch France
Ana I. Duarte Portugal
Lale Özcan United States
Hail Kim relative to Gu Seob Roh South Korea Gu Seob Roh's profile →
Citations per field
00.5×3.8×
Gu Seob Roh · 1×
Citations per year

Countries citing papers authored by Hail Kim

Since Specialization
Citations

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

Fields of papers citing papers by Hail Kim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 82 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Serotonin regulates pancreatic beta cell mass during pregnancy
Hit paper breakdown →
2010483
2 2017256
3 2015213
4 2004166
5 2013145
6 2011133
7 2018131
8 2018128
9 2014111
10 200599
11 201094
12 201294
13 201694
14 201592
15 200780
16 200080
17 201678
18 200974
19 201573
20 202362

About Hail Kim

Hail Kim is a scholar working on Molecular Biology, Surgery, Endocrinology, Diabetes and Metabolism, Epidemiology and Physiology, having authored 82 papers that have together received 4.0k indexed citations. Recurring topics across this work include Pancreatic function and diabetes (28 papers), Metabolism, Diabetes, and Cancer (11 papers), Adipose Tissue and Metabolism (9 papers), Diet, Metabolism, and Disease (9 papers), Liver Disease Diagnosis and Treatment (9 papers), Diabetes and associated disorders (8 papers), Peroxisome Proliferator-Activated Receptors (7 papers) and Neurotransmitter Receptor Influence on Behavior (7 papers). The work is most often cited by research in Biological Psychiatry (143 citations), Endocrinology, Diabetes and Metabolism (697 citations), Physiology (816 citations), Endocrine and Autonomic Systems (205 citations) and Surgery (1.2k citations). Hail Kim has collaborated with scholars based in South Korea, United States and Japan. Frequent co-authors include Yong‐Ho Ahn, Michael S. German, Chang‐Myung Oh, Jun Namkung, Seung‐Soon Im, Yasuhiro Kosaka, Sangkyu Park, Kyung‐Sup Kim, Takeshi Miyatsuka and Hyeongseok Kim. Their work appears in journals such as Nature Communications, Diabetes, Journal of Medicinal Chemistry, Experimental & Molecular Medicine and Diabetes & Metabolism Journal.

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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