Shigeto Seno

8.4k total citations
73 papers, 893 citations indexed

About

Shigeto Seno is a scholar working on Molecular Biology, Genetics and Cancer Research. According to data from OpenAlex, Shigeto Seno has authored 73 papers receiving a total of 893 indexed citations (citations by other indexed papers that have themselves been cited), including 43 papers in Molecular Biology, 9 papers in Genetics and 9 papers in Cancer Research. Recurrent topics in Shigeto Seno's work include Gene expression and cancer classification (9 papers), Gene Regulatory Network Analysis (7 papers) and Bacterial Genetics and Biotechnology (7 papers). Shigeto Seno is often cited by papers focused on Gene expression and cancer classification (9 papers), Gene Regulatory Network Analysis (7 papers) and Bacterial Genetics and Biotechnology (7 papers). Shigeto Seno collaborates with scholars based in Japan, South Korea and United States. Shigeto Seno's co-authors include Hideo Matsuda, Bei‐Wen Ying, Yoichi Takenaka, Masaru Ishii, Teruo Kawada, Tsuyoshi Goto, Junichi Kikuta, Tetsuya Yomo, Nobuyuki Takahashi and Haruya Takahashi and has published in prestigious journals such as Nucleic Acids Research, Journal of Biological Chemistry and Nature Communications.

In The Last Decade

Shigeto Seno

66 papers receiving 887 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Shigeto Seno Japan 17 487 190 139 131 82 73 893
Feiyu Zhang China 15 376 0.8× 142 0.7× 89 0.6× 56 0.4× 45 0.5× 61 1.0k
Bei Zhen China 17 645 1.3× 106 0.6× 84 0.6× 54 0.4× 72 0.9× 21 1.2k
Luciene Cristina Gastalho Campos Brazil 18 490 1.0× 75 0.4× 91 0.7× 76 0.6× 67 0.8× 37 1.1k
Huimin Hu China 17 385 0.8× 103 0.5× 76 0.5× 183 1.4× 26 0.3× 70 975
Giovanni Santacroce Italy 12 313 0.6× 166 0.9× 86 0.6× 184 1.4× 20 0.2× 61 737
Ivan Formentini Switzerland 12 535 1.1× 196 1.0× 85 0.6× 64 0.5× 20 0.2× 16 966
Shuming Sun China 21 566 1.2× 84 0.4× 72 0.5× 50 0.4× 49 0.6× 51 959
Qian Zhou China 19 470 1.0× 105 0.6× 119 0.9× 84 0.6× 18 0.2× 53 903
Gania Kessler‐Icekson Israel 21 754 1.5× 91 0.5× 67 0.5× 105 0.8× 29 0.4× 63 1.3k

Countries citing papers authored by Shigeto Seno

Since Specialization
Citations

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

Fields of papers citing papers by Shigeto Seno

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shigeto Seno

This figure shows the co-authorship network connecting the top 25 collaborators of Shigeto Seno. A scholar is included among the top collaborators of Shigeto Seno 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 Shigeto Seno. Shigeto Seno 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.
Tanei, Tomonori, Shigeto Seno, Tetsuhiro Yoshinami, et al.. (2025). High HER2 Intratumoral Heterogeneity Is Resistant to Anti-HER2 Neoadjuvant Chemotherapy in Early Stage and Locally Advanced HER2-Positive Breast Cancer. Cancers. 17(13). 2126–2126. 2 indexed citations
2.
Seno, Shigeto, Yasuto Naoi, Keiichiro Honma, et al.. (2025). IRSN-23 gene diagnosis enhances breast cancer subtype classification and predicts response to neoadjuvant chemotherapy: new validation analyses. Breast Cancer. 32(3). 566–581.
3.
Tanei, Tomonori, Shigeto Seno, Kaori Abe, et al.. (2024). High HER2 Intratumoral Heterogeneity Is a Predictive Factor for Poor Prognosis in Early-Stage and Locally Advanced HER2-Positive Breast Cancer. Cancers. 16(5). 1062–1062. 5 indexed citations
4.
Kim, Sang Eun, Yu‐Chen Liu, Yukari Nakajima, et al.. (2024). Novel integrated multiomics analysis reveals a key role for integrin beta-like 1 in wound scarring. EMBO Reports. 26(1). 122–152. 3 indexed citations
5.
Hosoda, Kazufumi, Shigeto Seno, & Tsutomu Murata. (2023). Simulating Reaction Time for Eureka Effect in Visual Object Recognition Using Artificial Neural Network. 3. 1–1. 1 indexed citations
6.
Ebihara, Takeshi, Tsunehiro Matsubara, Hisatake Matsumoto, et al.. (2022). Combination of WFDC2, CHI3L1, and KRT19 in Plasma Defines a Clinically Useful Molecular Phenotype Associated with Prognosis in Critically Ill COVID-19 Patients. Journal of Clinical Immunology. 43(2). 286–298. 10 indexed citations
7.
Kikuta, Junichi, Keizo Nishikawa, Takao Sudo, et al.. (2021). SLPI is a critical mediator that controls PTH-induced bone formation. Nature Communications. 12(1). 2136–2136. 31 indexed citations
8.
Yamashita, Erika, Shigeto Seno, Takao Sudo, et al.. (2020). Migration arrest of chemoresistant leukemia cells mediated by MRTF-SRF pathway. Inflammation and Regeneration. 40(1). 15–15. 7 indexed citations
9.
Seno, Shigeto, Takako Mukai, Yu‐Sheng Yeh, et al.. (2020). Glycerol kinase stimulates uncoupling protein 1 expression by regulating fatty acid metabolism in beige adipocytes. Journal of Biological Chemistry. 295(20). 7033–7045. 20 indexed citations
10.
Kim, Seung Jin, Yasuto Naoi, Keiichiro Honma, et al.. (2020). Determining homologous recombination deficiency scores with whole exome sequencing and their association with responses to neoadjuvant chemotherapy in breast cancer. Translational Oncology. 14(2). 100986–100986. 12 indexed citations
11.
Hasegawa, Tetsuo, Junichi Kikuta, Takao Sudo, et al.. (2020). Development of an intravital imaging system for the synovial tissue reveals the dynamics of CTLA-4 Ig in vivo. Scientific Reports. 10(1). 13480–13480. 15 indexed citations
12.
Nishikawa, Keizo, et al.. (2018). Roles of Enhancer RNAs in RANKL-induced Osteoclast Differentiation Identified by Genome-wide Cap-analysis of Gene Expression using CRISPR/Cas9. Scientific Reports. 8(1). 7504–7504. 15 indexed citations
13.
Takahashi, Haruya, Hiroyuki Nagai, Yongjia Li, et al.. (2017). Over-expression of PPARα in obese mice adipose tissue improves insulin sensitivity. Biochemical and Biophysical Research Communications. 493(1). 108–114. 19 indexed citations
14.
Ying, Bei‐Wen, Shigeto Seno, Hideo Matsuda, & Tetsuya Yomo. (2017). A simple comparison of the extrinsic noise in gene expression between native and foreign regulations in Escherichia coli. Biochemical and Biophysical Research Communications. 486(3). 852–857. 5 indexed citations
15.
Seno, Shigeto, et al.. (2016). Correlation between genome reduction and bacterial growth. DNA Research. 23(6). 517–525. 53 indexed citations
16.
Goto, Tsuyoshi, Yongjia Li, Tomoya Sakamoto, et al.. (2015). Proinflammatory cytokine interleukin-1β suppresses cold-induced thermogenesis in adipocytes. Cytokine. 77. 107–114. 98 indexed citations
17.
Yoshida, Mari, Saburo Tsuru, Shigeto Seno, et al.. (2014). Directed evolution of cell size in Escherichia coli. BMC Evolutionary Biology. 14(1). 257–257. 17 indexed citations
18.
Ying, Bei‐Wen, Saburo Tsuru, Shigeto Seno, Hideo Matsuda, & Tetsuya Yomo. (2013). Gene expression scaled by distance to the genome replication site. Molecular BioSystems. 10(3). 375–379. 18 indexed citations
19.
Seno, Shigeto, et al.. (2012). An estimation method for inference of gene regulatory net-work using Bayesian network with uniting of partial problems. BMC Genomics. 13(Suppl 1). S12–S12. 15 indexed citations
20.
Araki, Ryo, Shigeto Seno, Yoichi Takenaka, & Hideo Matsuda. (2012). An estimation method for a cellular-state-specific gene regulatory network along tree-structured gene expression profiles. Gene. 518(1). 17–25. 6 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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