Min An

21 papers receiving 671 citations

Peers

Min An
Comparison fields: 5 of 83
  • Cell Biology 141
  • Developmental Neuroscience 29
  • Molecular Biology 464
  • Cancer Research 97
  • Genetics 61
Replace Claire E. Monk with:
Claire E. Monk United Kingdom
Martina Vojtěchová Czechia
Terunao Takahara Japan
Lakshmi Pillai‐Kastoori United States
Peter J. Lyons United States
Eileithyia Swanton United Kingdom
Wenhao Yu China
Takashi Ishii Japan
Harald Mayer Austria
Christelle En Lin Chua Singapore
Min An relative to Claire E. Monk United Kingdom Claire E. Monk's profile →
Citations per field
00.5×3.5×
Claire E. Monk · 1×
Citations per year

Countries citing papers authored by Min An

Since Specialization
Citations

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

Fields of papers citing papers by Min An

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 23 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2001119
2 201087
3 201780
4 200278
5 200956
6 200941
7 201738
8 201738
9 201727
10 201227
11 200023
12 201615
13 202314
14 202211
15 202010
16 20124
17 20213
18 20183
19 20252
20
[Electrofusion of two-cell embryos of rabbit and their developmental capacity in vitro].
19931

About Min An

Min An is a scholar working on Molecular Biology, Pharmacology, Oncology, Immunology and Cancer Research, having authored 23 papers that have together received 679 indexed citations. Recurring topics across this work include Pharmacological Effects of Medicinal Plants (2 papers), MicroRNA in disease regulation (2 papers), Signaling Pathways in Disease (2 papers), Cancer Cells and Metastasis (2 papers), Genetic and Clinical Aspects of Sex Determination and Chromosomal Abnormalities (2 papers), RNA Research and Splicing (2 papers), Cancer-related molecular mechanisms research (2 papers) and Pancreatic and Hepatic Oncology Research (2 papers). The work is most often cited by research in Cell Biology (141 citations), Developmental Neuroscience (29 citations), Molecular Biology (464 citations), Cancer Research (97 citations) and Genetics (61 citations). Min An has collaborated with scholars based in United States, China and South Korea. Frequent co-authors include Paul D. Henion, Brigitte L. Arduini, Won Ho Kim, Tae Il Kim, Jae Hee Cheon, Seung Won Kim, Christine E. Beattie, Eun Soo Kim, Alessandra M. Welker and Jae Jun Park. Their work appears in journals such as Developmental Dynamics, International Journal of Oncology, Gastroenterology, British Journal of Cancer and The International Journal of Developmental Biology.

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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