Seiji Sakano

3.4k total citations
37 papers, 2.7k citations indexed

About

Seiji Sakano is a scholar working on Molecular Biology, Immunology and Cell Biology. According to data from OpenAlex, Seiji Sakano has authored 37 papers receiving a total of 2.7k indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Molecular Biology, 9 papers in Immunology and 5 papers in Cell Biology. Recurrent topics in Seiji Sakano's work include Developmental Biology and Gene Regulation (13 papers), Epigenetics and DNA Methylation (6 papers) and Zebrafish Biomedical Research Applications (4 papers). Seiji Sakano is often cited by papers focused on Developmental Biology and Gene Regulation (13 papers), Epigenetics and DNA Methylation (6 papers) and Zebrafish Biomedical Research Applications (4 papers). Seiji Sakano collaborates with scholars based in Japan, United States and Germany. Seiji Sakano's co-authors include Mickie Bhatia, Tomoyuki Miyabayashi, Masahide Koremoto, Lisa Gallacher, Barbara Murdoch, Akira Itoh, Douglas A. Gray, David J. Hill, Matthew A. Martin and S. M. Thyssen and has published in prestigious journals such as Journal of Biological Chemistry, The Journal of Experimental Medicine and Blood.

In The Last Decade

Seiji Sakano

37 papers receiving 2.7k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Seiji Sakano Japan 25 1.6k 670 448 412 386 37 2.7k
Christopher B. Brown United States 28 1.8k 1.1× 318 0.5× 342 0.8× 381 0.9× 110 0.3× 61 2.7k
Ernst Pöschl Germany 32 2.0k 1.2× 529 0.8× 257 0.6× 212 0.5× 219 0.6× 66 3.8k
Frederick W. Jacobsen United States 13 1.1k 0.7× 637 1.0× 140 0.3× 355 0.9× 181 0.5× 20 2.1k
Jennifer J. Hofmann United States 18 2.2k 1.4× 420 0.6× 366 0.8× 248 0.6× 166 0.4× 24 3.5k
Ann Johnsson Sweden 7 1.6k 1.0× 350 0.5× 217 0.5× 254 0.6× 193 0.5× 7 2.6k
Mark Lupher United States 27 1.6k 1.0× 1.3k 2.0× 236 0.5× 226 0.5× 239 0.6× 38 3.4k
D B Rifkin United States 21 2.2k 1.4× 276 0.4× 379 0.8× 474 1.2× 163 0.4× 26 3.7k
Tomoko Nakanishi Japan 4 1.3k 0.8× 353 0.5× 351 0.8× 116 0.3× 412 1.1× 9 2.5k
Fred Sablitzky United Kingdom 30 2.0k 1.3× 1.2k 1.8× 166 0.4× 235 0.6× 185 0.5× 48 3.4k
Yves Eeckhout Belgium 34 1.2k 0.8× 786 1.2× 247 0.6× 718 1.7× 438 1.1× 64 4.1k

Countries citing papers authored by Seiji Sakano

Since Specialization
Citations

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

Fields of papers citing papers by Seiji Sakano

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Seiji Sakano

This figure shows the co-authorship network connecting the top 25 collaborators of Seiji Sakano. A scholar is included among the top collaborators of Seiji Sakano 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 Seiji Sakano. Seiji Sakano 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.
Fukushima, Hidefumi, Kouhei Shimizu, Tomoki Kosho, et al.. (2017). NOTCH2 Hajdu-Cheney Mutations Escape SCFFBW7-Dependent Proteolysis to Promote Osteoporosis. Molecular Cell. 68(4). 645–658.e5. 30 indexed citations
2.
Murata, Akihiko, Miya Yoshino, Kazuki Okuyama, et al.. (2014). An Evolutionary-Conserved Function of Mammalian Notch Family Members as Cell Adhesion Molecules. PLoS ONE. 9(9). e108535–e108535. 14 indexed citations
3.
Murata, Akihiko, Kazuki Okuyama, Seiji Sakano, et al.. (2010). A Notch Ligand, Delta-Like 1 Functions As an Adhesion Molecule for Mast Cells. The Journal of Immunology. 185(7). 3905–3912. 31 indexed citations
4.
Haraguchi, Kyoko, Takahiro Suzuki, Noriko Koyama, et al.. (2009). Notch Activation Induces the Generation of Functional NK Cells from Human Cord Blood CD34-Positive Cells Devoid of IL-15. The Journal of Immunology. 182(10). 6168–6178. 41 indexed citations
5.
Yatim, Ahmad, Clarisse Benne, Adeline Henry, et al.. (2009). Notch ligands potentiate IL‐7‐driven proliferation and survival of human thymocyte precursors. European Journal of Immunology. 39(5). 1231–1240. 33 indexed citations
6.
Fukushima, Hidefumi, Akihiro Nakao, Fujio Okamoto, et al.. (2008). The Association of Notch2 and NF-κB Accelerates RANKL-Induced Osteoclastogenesis. Molecular and Cellular Biology. 28(20). 6402–6412. 149 indexed citations
7.
Miyabayashi, Tomoyuki, Masashi Yamamoto, Akiko Satô, Seiji Sakano, & Yasuyuki Takahashi. (2008). Indole Derivatives Sustain Embryonic Stem Cell Self-Renewal in Long-Term Culture. Bioscience Biotechnology and Biochemistry. 72(5). 1242–1248. 12 indexed citations
8.
Tohda, Shuji, et al.. (2006). Establishment of a novel B-cell lymphoma cell line with suppressed growth by gamma-secretase inhibitors. Leukemia Research. 30(11). 1385–1390. 35 indexed citations
9.
Konno, Tomohiro, Seiji Sakano, Shuji Tohda, & Yoshihiro Ito. (2005). Preparation of polymer matrix bioconjugated with Notch ligand. 25(5). 426–430. 1 indexed citations
10.
Rutz, Sascha, Benjamin Mordmüller, Seiji Sakano, & Alexander Scheffold. (2005). Notch ligands Delta-like1, Delta-like4 and Jagged1 differentially regulate activation of peripheral T helper cells. European Journal of Immunology. 35(8). 2443–2451. 90 indexed citations
11.
Tohda, Shuji, et al.. (2005). Diverse effects of the Notch ligands Jagged1 and Delta1 on the growth and differentiation of primary acute myeloblastic leukemia cells. Experimental Hematology. 33(5). 558–563. 44 indexed citations
12.
13.
Hess, David A., Li Li, Matthew A. Martin, et al.. (2003). Bone marrow–derived stem cells initiate pancreatic regeneration. Nature Biotechnology. 21(7). 763–770. 485 indexed citations
14.
Yamada, Takayuki, Hidetoshi Yamazaki, Toshiyuki Yamane, et al.. (2003). Regulation of osteoclast development by Notch signaling directed to osteoclast precursors and through stromal cells. Blood. 101(6). 2227–2234. 102 indexed citations
15.
Masuya, Masahiro, Naoyuki Katayama, Hiroyoshi Nishikawa, et al.. (2002). The Soluble Notch Ligand, Jagged-1, Inhibits Proliferation of CD34+ Macrophage Progenitors. International Journal of Hematology. 75(3). 269–276. 35 indexed citations
16.
Nishizumi, Hirofumi, Takaki Komiyama, Tomoyuki Miyabayashi, Seiji Sakano, & Hitoshi Sakano. (2002). BET, a novel neuronal transmembrane protein with multiple EGF-like motifs. Neuroreport. 13(6). 909–915. 12 indexed citations
17.
Murdoch, Barbara, Lisa Gallacher, Dongmei Wu, et al.. (2000). The Notch Ligand Jagged-1 Represents a Novel Growth Factor of Human Hematopoietic Stem Cells. The Journal of Experimental Medicine. 192(9). 1365–1372. 337 indexed citations
18.
Shibuya, Akira, Norihisa Sakamoto, Yoshio Shimizu, et al.. (2000). Fcα/μ receptor mediates endocytosis of IgM-coated microbes. Nature Immunology. 1(5). 441–446. 300 indexed citations
19.
20.
Hamaguchi, Isao, Atsushi Iwama, Naoto Yamaguchi, et al.. (1994). Characterization of mouse non-receptor tyrosine kinase gene, HYL.. PubMed. 9(11). 3371–4. 12 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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