Tatsuya Takemoto

3.7k citations
73 papers · 2.7k indexed · h-index 24

Tatsuya Takemoto

67 papers receiving 2.7k citations

Peers

Tatsuya Takemoto
Comparison fields: 5 of 118
  • Developmental Neuroscience 141
  • Aging 47
  • Molecular Biology 1.7k
  • Genetics 656
  • Business and International Management 43
Replace Niels Geijsen with:
Niels Geijsen Netherlands
Xiaoping Bao United States
Xiaojun Lian United States
Kye-Seong Kim South Korea
Carol-Anne Martin United Kingdom
Sara E. Howden Australia
Albert J. Keung United States
Lei Bu United States
Mark D. Brigham United States
Hirofumi Suemori Japan
Tatsuya Takemoto relative to Niels Geijsen Netherlands Niels Geijsen's profile →
Citations per field
00.5×1.6×
Niels Geijsen · 1×
Citations per year

Countries citing papers authored by Tatsuya Takemoto

Since Specialization
Citations

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

Fields of papers citing papers by Tatsuya Takemoto

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20250
2 20242
3 20240
4 20238
5 20238
6 2022129
7 202257
8 202114
9 202110
10 2019285
11 201824
12 201731
13 201696
14 2015251
15
Effect of heating method on microstructure of Sn-3.0Ag-0.5Cu solder on Cu substrate
20118
16 201055
17
Characteristics of electrically conductive adhesives filled with copper nanoparticles with organic layer
20092
18 2005117
19 200469
20 2003312

About Tatsuya Takemoto

Tatsuya Takemoto is a scholar working on General Materials Science, Aging, Molecular Biology, Business and International Management and Genetics, having authored 73 papers that have together received 2.7k indexed citations. Recurring topics across this work include Pluripotent Stem Cells Research (16 papers), Electronic Packaging and Soldering Technologies (15 papers), Developmental Biology and Gene Regulation (13 papers), Animal Genetics and Reproduction (12 papers), Congenital heart defects research (10 papers), CRISPR and Genetic Engineering (9 papers), Genetic and Clinical Aspects of Sex Determination and Chromosomal Abnormalities (5 papers) and 3D IC and TSV technologies (5 papers). The work is most often cited by research in Developmental Neuroscience (141 citations), Aging (47 citations), Molecular Biology (1.7k citations), Genetics (656 citations) and Business and International Management (43 citations). Tatsuya Takemoto has collaborated with scholars based in Japan, China and United Kingdom. Frequent co-authors include Hisato Kondoh, Masakazu Hashimoto, Masanori Uchikawa, Yusuke Kamachi, Feng Gao, Hiroshi Nishikawa, Yoshiko Ishida, Yukiko Yamashita, Il‐mi Okazaki and Taku Okazaki. Their work appears in journals such as Developmental Biology, Development Growth & Differentiation, Nature Communications, Mechanisms of Development and Genes to Cells.

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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