Takahiro Arima

125 papers receiving 4.4k citations

Hit Papers

Derivation of Human Trophoblast Stem Cells2017202620202023201720242024200400600

Peers

Takahiro Arima
Comparison fields: 5 of 130
  • Molecular Biology 2.4k
  • Pediatrics, Perinatology and Child Health 1.8k
  • Genetics 1.2k
  • Obstetrics and Gynecology 1.0k
  • Public Health, Environmental and Occupational Health 847
Replace Simon C. Riley with:
Simon C. Riley United Kingdom
Pao‐Lin Kuo Taiwan
Harvey J. Kliman United States
Mana M. Parast United States
Lorraine Young United Kingdom
Clifford Librach Canada
Deborah E. McFadden Canada
Takeshi Maruo Japan
Kiyonori Miura Japan
P. Bischof Switzerland
Takahiro Arima relative to Simon C. Riley United Kingdom Simon C. Riley's profile →
Citations per field
00.5×11×
Simon C. Riley · 1×
Citations per year

Countries citing papers authored by Takahiro Arima

Since Specialization
Citations

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

Fields of papers citing papers by Takahiro Arima

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Takahiro Arima

This figure shows the co-authorship network connecting the top 25 collaborators of Takahiro Arima. A scholar is included among the top collaborators of Takahiro Arima based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Takahiro Arima. Takahiro Arima is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
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Modeling embryo-endometrial interface recapitulating human embryo implantationbreakdown →
51
3 9
4 18
5 2
6 17
7 17
8 6
9 3
10 40
11 10
12 21
13 12
14 4
15 16
16 10
17 14
18 14
19 23
20 42

About Takahiro Arima

Takahiro Arima is a scholar working on Obstetrics and Gynecology, Pediatrics, Perinatology and Child Health and Genetics, having authored 137 papers that have together received 4.4k indexed citations. Recurring topics across this work include Epigenetics and DNA Methylation (36 papers), Prenatal Screening and Diagnostics (34 papers) and Genetic Syndromes and Imprinting (33 papers). The work is most often cited by research in Obstetrics and Gynecology (1.0k citations), Pediatrics, Perinatology and Child Health (1.8k citations) and Reproductive Medicine (639 citations). Takahiro Arima has collaborated with scholars based in Japan, United States and United Kingdom. Frequent co-authors include Hiroaki Okae, Hitoshi Hiura, Nobuo Yaegashi, Akiko Satô, Norio Wake, Mikita Suyama, Hiroyuki Sasaki, Takafumi Utsunomiya, Hidehiro Toh and Tetsuya Sato. Their work appears in journals such as Proceedings of the National Academy of Sciences, Journal of the American Chemical Society and Nucleic Acids 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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