Satoshi Terada

2.9k total citations
89 papers, 1.8k citations indexed

About

Satoshi Terada is a scholar working on Molecular Biology, Surgery and Genetics. According to data from OpenAlex, Satoshi Terada has authored 89 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 40 papers in Molecular Biology, 19 papers in Surgery and 13 papers in Genetics. Recurrent topics in Satoshi Terada's work include Viral Infectious Diseases and Gene Expression in Insects (23 papers), Neuroscience and Neuropharmacology Research (9 papers) and Silk-based biomaterials and applications (8 papers). Satoshi Terada is often cited by papers focused on Viral Infectious Diseases and Gene Expression in Insects (23 papers), Neuroscience and Neuropharmacology Research (9 papers) and Silk-based biomaterials and applications (8 papers). Satoshi Terada collaborates with scholars based in Japan, United States and Hungary. Satoshi Terada's co-authors include Masahiro Sasaki, Hideyuki Yamada, Freddie H. Fu, Johnny Huard, Kana Yanagihara, Shusuke Ota, Yoshio Sakurai, Shigeyoshi Fujisawa, Hiroyuki Nakahara and Hidemitsu Kitamura and has published in prestigious journals such as Nature, Science and Neuron.

In The Last Decade

Satoshi Terada

87 papers receiving 1.8k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Satoshi Terada Japan 22 602 387 335 320 320 89 1.8k
Mitchell A. Watsky United States 29 1.5k 2.5× 579 1.5× 337 1.0× 628 2.0× 69 0.2× 86 4.3k
Dorothy M. Supp United States 32 1.6k 2.6× 682 1.8× 559 1.7× 99 0.3× 156 0.5× 101 3.8k
Tor Paaske Utheim Norway 39 1.1k 1.8× 143 0.4× 265 0.8× 239 0.7× 75 0.2× 311 5.1k
Haitao Wu China 30 1.2k 2.1× 146 0.4× 114 0.3× 638 2.0× 195 0.6× 120 3.1k
Seok Jong Hong United States 30 1.2k 2.0× 124 0.3× 355 1.1× 345 1.1× 39 0.1× 83 2.6k
Tetsuya Goto Japan 32 1.2k 2.0× 86 0.2× 261 0.8× 462 1.4× 106 0.3× 102 2.9k
Johannes Kacza Germany 24 663 1.1× 142 0.4× 142 0.4× 590 1.8× 110 0.3× 64 2.0k
Deborah Watson United States 37 1.3k 2.2× 307 0.8× 1.1k 3.2× 946 3.0× 217 0.7× 140 4.1k
David L. Becker United Kingdom 29 1.4k 2.3× 94 0.2× 174 0.5× 253 0.8× 42 0.1× 73 2.3k
Catherine M. Cowan United States 33 1.6k 2.6× 257 0.7× 640 1.9× 846 2.6× 35 0.1× 55 3.7k

Countries citing papers authored by Satoshi Terada

Since Specialization
Citations

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

Fields of papers citing papers by Satoshi Terada

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Satoshi Terada

This figure shows the co-authorship network connecting the top 25 collaborators of Satoshi Terada. A scholar is included among the top collaborators of Satoshi Terada 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 Satoshi Terada. Satoshi Terada 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
1.
Liao, Zhenrui, Satoshi Terada, Ivan Raikov, et al.. (2024). Inhibitory plasticity supports replay generalization in the hippocampus. Nature Neuroscience. 27(10). 1987–1998. 4 indexed citations
2.
Gonzalez, Kevin C., Adrian Negrean, Zhenrui Liao, et al.. (2024). Synaptic basis of feature selectivity in hippocampal neurons. Nature. 637(8048). 1152–1160. 9 indexed citations
3.
Ogawa, Akiko, et al.. (2023). Antibiofilm Property and Biocompatibility of Siloxane-Based Polymer Coatings Applied to Biomaterials. Materials. 16(23). 7399–7399. 2 indexed citations
4.
Farrell, Jordan S., Matthew Lovett-Barron, Peter Klein, et al.. (2021). Supramammillary regulation of locomotion and hippocampal activity. Science. 374(6574). 1492–1496. 40 indexed citations
5.
Ogawa, Akiko, et al.. (2020). Biofilm Formation Plays a Crucial Rule in the Initial Step of Carbon Steel Corrosion in Air and Water Environments. Materials. 13(4). 923–923. 29 indexed citations
6.
7.
Yokoi, S., Makoto Murakami, Mitsuhiro Morikawa, et al.. (2016). Sericin in the isolating solution improves the yield of islets isolated from the pancreas. Cytotechnology. 68(6). 2491–2502. 7 indexed citations
8.
Sakurai, Yoshio, et al.. (2013). Diverse synchrony of firing reflects diverse cell-assembly coding in the prefrontal cortex. Journal of Physiology-Paris. 107(6). 459–470. 13 indexed citations
9.
Terada, Satoshi, et al.. (2011). A Case of Degloving Injury of the Whole Hand Reconstructed by a Combination of Distant Flaps Comprising an Anterolateral Thigh Flap and a Groin Flap. Journal of Reconstructive Microsurgery. 27(5). 299–302. 7 indexed citations
10.
Ikegami, Y., Alasdair W. Clark, Satoshi Terada, et al.. (2009). Development of low-mass, high-density, hybrid circuit for the silicon microstrip sensors in high track density environment. 21. 1 indexed citations
11.
Ogawa, Akiko, Naoki Takada, & Satoshi Terada. (2009). Effective Antibody Production by Reusing Culture Medium Previously Used in Antibody Purification. Bioscience Biotechnology and Biochemistry. 73(3). 719–721. 6 indexed citations
12.
Morikawa, Mitsuhiro, Toshihisa Kimura, Makoto Murakami, et al.. (2009). Rat islet culture in serum-free medium containing silk protein sericin. Journal of Hepato-Biliary-Pancreatic Surgery. 16(2). 223–228. 29 indexed citations
13.
Yanagihara, Kana, Satoshi Terada, Masao Miki, Masahiro Sasaki, & Hideyuki Yamada. (2006). Effect of the silk protein sericin on the production of adenovirus‐based gene‐therapy vectors. Biotechnology and Applied Biochemistry. 45(2). 59–64. 13 indexed citations
14.
Wu, Xing‐Zheng & Satoshi Terada. (2005). Noninvasive Diagnosis of a Single Cell with a Probe Beam. Biotechnology Progress. 21(6). 1772–1774. 8 indexed citations
15.
Yanagihara, Kana, et al.. (2004). Silk Protein Sericin : as a Novel Mitogenic Supplement for Mammalian Cell Culture. 2004. 493–493. 1 indexed citations
16.
Kawahara, Masahiro, Akito Natsume, Satoshi Terada, et al.. (2001). Replacing factor‐dependency with that for lysozyme: Affordable culture of IL‐6‐dependent hybridoma by transfecting artificial cell surface receptor. Biotechnology and Bioengineering. 74(5). 416–423. 13 indexed citations
17.
Terada, Satoshi, et al.. (1998). Erratum: Establishing apoptosis resistant cell lines for improving protein productivity of cell culture. Cytotechnology. 26(1). 79–79. 6 indexed citations
18.
Suzuki, Eiji, Satoshi Terada, Hiroshi Ueda, et al.. (1997). Establishing apoptosis resistant cell lines for improving protein productivity of cell culture. Cytotechnology. 23(1-3). 55–59. 19 indexed citations
19.
Terada, Satoshi, et al.. (1997). Characterization and fed-batch culture of hybridoma overexpressing apoptosis suppressing gene bcl-2. Cytotechnology. 24(2). 135–141. 10 indexed citations
20.
Makishima, Fusao, et al.. (1992). Interleukin-6 is antiproliferative to a mouse hybridoma cell line and promotive for its antibody productivity. Cytotechnology. 10(1). 15–23. 29 indexed citations

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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