Mi Jin Moon

963 citations
21 papers · 802 · h-index 16

Impact in

Papers in

Mi Jin Moon

21 papers receiving 792 citations

Peers

Mi Jin Moon
Comparison fields: 5 of 66
  • Reproductive Medicine 291
  • Physiology 99
  • Cellular and Molecular Neuroscience 234
  • Endocrinology, Diabetes and Metabolism 146
  • Endocrine and Autonomic Systems 57
Replace Maïté Montero‐Hadjadje with:
Maïté Montero‐Hadjadje France
Ke-Wen Dong United States
Kyungjin Kim South Korea
Krishan K. Arora United States
Sho Nakamura Japan
Nobuhiro Harada Japan
Eun Bee Cho South Korea
Yuji Inomata Japan
Fredric R. Boockfor United States
Christine Glidewell-Kenney United States
Mi Jin Moon relative to Maïté Montero‐Hadjadje France Maïté Montero‐Hadjadje's profile →
Citations per field
00.5×1.5×
Maïté Montero‐Hadjadje · 1×
Citations per year

Countries citing papers authored by Mi Jin Moon

Since Specialization
Citations

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

Fields of papers citing papers by Mi Jin Moon

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mi Jin Moon. 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 Mi Jin Moon. The network helps show where Mi Jin Moon may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 21 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2009191
2 2008114
3 201083
4 201347
5 201243
6 200436
7 201235
8 200634
9 201327
10 201426
11 201222
12 201522
13 201419
14 201418
15 201118
16 200718
17 201015
18 201414
19 201110
20 20187

About Mi Jin Moon

Mi Jin Moon is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience, Endocrinology, Diabetes and Metabolism, Reproductive Medicine and Surgery, having authored 21 papers that have together received 802 indexed citations. Recurring topics across this work include Receptor Mechanisms and Signaling (11 papers), Diabetes Treatment and Management (8 papers), Hypothalamic control of reproductive hormones (6 papers), Neuropeptides and Animal Physiology (6 papers), Genetic and Clinical Aspects of Sex Determination and Chromosomal Abnormalities (4 papers), Plant Reproductive Biology (3 papers), Pancreatic function and diabetes (3 papers) and Peptidase Inhibition and Analysis (2 papers). The work is most often cited by research in Reproductive Medicine (291 citations), Physiology (99 citations), Cellular and Molecular Neuroscience (234 citations), Endocrinology, Diabetes and Metabolism (146 citations) and Endocrine and Autonomic Systems (57 citations). Mi Jin Moon has collaborated with scholars based in South Korea, France and United States. Frequent co-authors include Jae Young Seong, Jong‐Ik Hwang, Hyuk Bang Kwon, Hubert Vaudry, Eun Bee Cho, Sumi Park, Da Young Oh, Kazuyoshi Tsutsui, Kenta Tsunekawa and Tomohiro Osugi. Their work appears in journals such as Journal of Biological Chemistry, General and Comparative Endocrinology, Molecules and Cells, PLoS ONE and Molecular Biology and Evolution.

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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