Seiya Imoto

28.4k total citations · 3 hit papers
284 papers, 7.0k citations indexed

About

Seiya Imoto is a scholar working on Molecular Biology, Oncology and Cancer Research. According to data from OpenAlex, Seiya Imoto has authored 284 papers receiving a total of 7.0k indexed citations (citations by other indexed papers that have themselves been cited), including 163 papers in Molecular Biology, 37 papers in Oncology and 34 papers in Cancer Research. Recurrent topics in Seiya Imoto's work include Bioinformatics and Genomic Networks (66 papers), Gene expression and cancer classification (63 papers) and Gene Regulatory Network Analysis (46 papers). Seiya Imoto is often cited by papers focused on Bioinformatics and Genomic Networks (66 papers), Gene expression and cancer classification (63 papers) and Gene Regulatory Network Analysis (46 papers). Seiya Imoto collaborates with scholars based in Japan, United States and Australia. Seiya Imoto's co-authors include Satoru Miyano, Rui Yamaguchi, Teppei Shimamura, Takao Goto, Kohichi Kawahara, Masaki Mori, Kohei Shibata, Fumiaki Tanaka, Koshi Mimori and Ryunosuke Kogo and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and Nucleic Acids Research.

In The Last Decade

Seiya Imoto

267 papers receiving 6.8k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Long Noncoding RNA HOTAIR Regulates Polycomb-Dependent Chromatin Modification and Is Associated with Poor Prognosis in Colorectal Cancers

2011 1.1k citations Ryunosuke Kogo, Teppei Shimamura et al. Cancer Research profile →
Blautia genus associated with visceral fat accumulation in adults 20–76 years of age

2019 285 citations Itoyo Tokuda, Kaori Sawada et al. npj Biofilms and Microbiomes profile →
Blocking PD-L1–PD-1 improves senescence surveillance and ageing phenotypes

2022 278 citations Kiyoshi Yamaguchi, Seira Hatakeyama et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Seiya Imoto Japan	39	4.5k	1.6k	693	622	587	284	7.0k
Tao Huang China	50	6.0k 1.3×	1.5k 0.9×	569 0.8×	443 0.7×	410 0.7×	395	8.7k
Youping Deng United States	46	3.8k 0.8×	1.1k 0.7×	552 0.8×	389 0.6×	418 0.7×	245	6.7k
Mario Medvedovic United States	48	3.8k 0.9×	1.4k 0.9×	779 1.1×	674 1.1×	286 0.5×	162	6.9k
Yu‐Dong Cai China	64	11.8k 2.6×	1.5k 0.9×	674 1.0×	461 0.7×	545 0.9×	491	15.6k
Michael Reich United States	22	6.5k 1.4×	1.3k 0.8×	1.2k 1.7×	1.0k 1.7×	699 1.2×	42	9.6k
Lei Chen China	48	5.4k 1.2×	1.2k 0.7×	388 0.6×	441 0.7×	455 0.8×	338	8.1k
Rainer Spang Germany	40	4.6k 1.0×	913 0.6×	1.6k 2.3×	702 1.1×	407 0.7×	148	7.3k
Tero Aittokallio Finland	54	6.3k 1.4×	1.1k 0.7×	1.4k 2.0×	1.1k 1.8×	299 0.5×	244	10.2k
Jan Komorowski Poland	38	4.2k 0.9×	1.3k 0.8×	566 0.8×	449 0.7×	701 1.2×	224	6.9k
Julio Sáez-Rodríguez Germany	58	8.9k 2.0×	1.2k 0.8×	1.1k 1.6×	1.2k 1.9×	342 0.6×	249	12.4k

Countries citing papers authored by Seiya Imoto

Since Specialization

Citations

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

Fields of papers citing papers by Seiya Imoto

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Seiya Imoto

This figure shows the co-authorship network connecting the top 25 collaborators of Seiya Imoto. A scholar is included among the top collaborators of Seiya Imoto 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 Seiya Imoto. Seiya Imoto is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Nakamura, Yusuke, Kazuma Kiyotani, Seiya Imoto, et al.. (2024). Comparative analysis of the B cell receptor repertoire during relapse and remission in patients with multiple sclerosis. Clinical Immunology. 269. 110398–110398. 2 indexed citations

Kuwatsuka, Yachiyo, Rika Kasajima, Rui Yamaguchi, et al.. (2024). Machine Learning Prediction Model for Neutrophil Recovery after Unrelated Cord Blood Transplantation. Transplantation and Cellular Therapy. 30(4). 444.e1–444.e11. 1 indexed citations

Uneda, Kazushi, Tetsuhiro Yoshino, Hidenori Ito, Seiya Imoto, & Tatsuya Nogami. (2024). Current situation and future issues with Kampo medicine: A survey of Japanese physicians. Traditional & Kampo Medicine. 11(2). 156–166. 10 indexed citations

Wang, Zhikang, Chris Bain, Seiya Imoto, et al.. (2024). Dual-stream multi-dependency graph neural network enables precise cancer survival analysis. Medical Image Analysis. 97. 103252–103252. 14 indexed citations

Murakami, Michio, et al.. (2023). Sensitivity of rapid antigen tests for COVID-19 during the Omicron variant outbreak among players and staff members of the Japan Professional Football League and clubs: a retrospective observational study. BMJ Open. 13(1). e067591–e067591. 6 indexed citations

Yokoyama, Kazuaki, et al.. (2023). Explainable AI for Estimating Pathogenicity of Genetic Variants Using Large-Scale Knowledge Graphs. Cancers. 15(4). 1118–1118. 11 indexed citations

Saito, Hiroaki, Makoto Yoshida, Tianchen Zhao, et al.. (2023). Antibody Profiling of Microbial Antigens in the Blood of COVID-19 mRNA Vaccine Recipients Using Microbial Protein Microarrays. Vaccines. 11(11). 1694–1694. 1 indexed citations

Imoto, Seiya, et al.. (2023). Comprehensive information-based differential gene regulatory networks analysis (CIdrgn): Application to gastric cancer and chemotherapy-responsive gene network identification. PLoS ONE. 18(8). e0286044–e0286044. 2 indexed citations

Li, Chen, Yue Bi, Zhikang Wang, et al.. (2023). PFresGO: an attention mechanism-based deep-learning approach for protein annotation by integrating gene ontology inter-relationships. Bioinformatics. 39(3). 27 indexed citations

10.

Wang, Qingbo S., Ryuya Edahiro, Ho Namkoong, et al.. (2023). Estimating gene-level false discovery probability improves eQTL statistical fine-mapping precision. NAR Genomics and Bioinformatics. 5(4). lqad090–lqad090.

11.

Hasegawa, Takanori, Masanori Kakuta, Rui Yamaguchi, et al.. (2022). Impact of salivary and pancreatic amylase gene copy numbers on diabetes, obesity, and functional profiles of microbiome in Northern Japanese population. Scientific Reports. 12(1). 7 indexed citations

12.

Ogawa, Miho, Kazuaki Yokoyama, Seiya Imoto, & Arinobu Tojo. (2021). Role of Circulating Tumor DNA in Hematological Malignancy. Cancers. 13(9). 2078–2078. 14 indexed citations

13.

Kakuta, Masanori, Takanori Hasegawa, Rui Yamaguchi, et al.. (2020). Metagenomic analysis of bacterial species in tongue microbiome of current and never smokers. npj Biofilms and Microbiomes. 6(1). 39 indexed citations

14.

Konishi, Hiroki, Rui Yamaguchi, Kiyoshi Yamaguchi, Yoichi Furukawa, & Seiya Imoto. (2020). Halcyon: an accurate basecaller exploiting an encoder–decoder model with monotonic attention. Bioinformatics. 37(9). 1211–1217. 14 indexed citations

15.

Muraoka, Daisuke, Naohiro Seo, Tae Hayashi, et al.. (2019). Antigen delivery targeted to tumor-associated macrophages overcomes tumor immune resistance. Journal of Clinical Investigation. 129(3). 1278–1294. 117 indexed citations

16.

Yamaguchi, Kiyoshi, Eigo Shimizu, Rui Yamaguchi, et al.. (2019). Development of an MSI-positive colon tumor with aberrant DNA methylation in a PPAP patient. Journal of Human Genetics. 64(8). 729–740. 7 indexed citations

17.

Yokoyama, Kazuaki, Eigo Shimizu, Miho Ogawa, et al.. (2019). Prognostic impact of circulating tumor DNA status post–allogeneic hematopoietic stem cell transplantation in AML and MDS. Blood. 133(25). 2682–2695. 71 indexed citations

18.

Hayashi, Shuto, Rui Yamaguchi, Shinichi Mizuno, et al.. (2018). ALPHLARD: a Bayesian method for analyzing HLA genes from whole genome sequence data. BMC Genomics. 19(1). 16 indexed citations

19.

Yoshino, Tetsuhiro, Kotoe Katayama, K Munakata, et al.. (2014). Kampo Traditional Pattern Diagnosis and the Clustering Analysis of Patients with Cold Sensation. The Journal of Alternative and Complementary Medicine. 20(5). A47–A47. 1 indexed citations

20.

Kogo, Ryunosuke, Teppei Shimamura, Koshi Mimori, et al.. (2011). Long Noncoding RNA HOTAIR Regulates Polycomb-Dependent Chromatin Modification and Is Associated with Poor Prognosis in Colorectal Cancers. Cancer Research. 71(20). 6320–6326. 1070 indexed citations breakdown →

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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