Seishi Ogawa

55.3k total citations · 3 hit papers
474 papers, 16.1k citations indexed

About

Seishi Ogawa is a scholar working on Hematology, Molecular Biology and Immunology. According to data from OpenAlex, Seishi Ogawa has authored 474 papers receiving a total of 16.1k indexed citations (citations by other indexed papers that have themselves been cited), including 215 papers in Hematology, 191 papers in Molecular Biology and 99 papers in Immunology. Recurrent topics in Seishi Ogawa's work include Acute Myeloid Leukemia Research (160 papers), Hematopoietic Stem Cell Transplantation (48 papers) and Immune Cell Function and Interaction (44 papers). Seishi Ogawa is often cited by papers focused on Acute Myeloid Leukemia Research (160 papers), Hematopoietic Stem Cell Transplantation (48 papers) and Immune Cell Function and Interaction (44 papers). Seishi Ogawa collaborates with scholars based in Japan, United States and Sweden. Seishi Ogawa's co-authors include Hisamaru Hirai, Mineo Kurokawa, Shigeru Chiba, Masashi Sanada, Kinuko Mitani, Kenichi Yoshida, Y Yazaki, Yasuhito Nannya, Akira Hangaishi and Hiroyuki Mano and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and Nucleic Acids Research.

In The Last Decade

Seishi Ogawa

448 papers receiving 15.9k citations

Hit Papers

align trajectories sort by overperformance

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.

Oncogenic mutations of ALK kinase in neuroblastoma

2008 640 citations Motohiro Kato, Masashi Sanada et al. profile →
A novel signaling molecule, p130, forms stable complexes in vivo with v-Crk and v-Src in a tyrosine phosphorylation-dependent manner.

1994 582 citations Seishi Ogawa et al. profile →
A Robust Algorithm for Copy Number Detection Using High-Density Oligonucleotide Single Nucleotide Polymorphism Genotyping Arrays

2005 501 citations Yasuhito Nannya, Masashi Sanada et al. Cancer Research profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Seishi Ogawa Japan	69	8.3k	5.1k	3.0k	2.8k	2.4k	474	16.1k
Ramesh A. Shivdasani United States	76	9.8k 1.2×	3.9k 0.8×	1.8k 0.6×	3.6k 1.3×	1.8k 0.7×	180	17.3k
Yoshiaki Ito Japan	74	12.5k 1.5×	3.8k 0.7×	2.5k 0.8×	4.8k 1.7×	3.0k 1.3×	422	19.4k
Warren S. Pear United States	74	11.7k 1.4×	3.3k 0.6×	5.4k 1.8×	3.1k 1.1×	1.7k 0.7×	181	18.8k
Mineo Kurokawa Japan	57	6.0k 0.7×	5.2k 1.0×	1.8k 0.6×	2.1k 0.8×	1.0k 0.4×	455	12.8k
Michael L. Cleary United States	84	15.3k 1.8×	5.6k 1.1×	3.0k 1.0×	4.3k 1.6×	1.5k 0.6×	206	23.2k
R. Keith Humphries Canada	85	13.0k 1.6×	7.5k 1.5×	4.7k 1.5×	3.2k 1.2×	1.9k 0.8×	314	21.5k
Terence H. Rabbitts United Kingdom	80	11.5k 1.4×	3.5k 0.7×	5.8k 1.9×	3.3k 1.2×	1.3k 0.5×	280	19.6k
Hisamaru Hirai Japan	71	9.1k 1.1×	3.8k 0.8×	3.6k 1.2×	3.2k 1.2×	1.2k 0.5×	302	17.1k
Brigitte Schlegelberger Germany	66	7.8k 0.9×	6.7k 1.3×	1.9k 0.6×	2.9k 1.1×	2.6k 1.1×	395	16.3k
Gerard C. Grosveld United States	65	10.8k 1.3×	6.8k 1.3×	4.7k 1.5×	6.6k 2.4×	1.8k 0.7×	158	21.9k

Countries citing papers authored by Seishi Ogawa

Since Specialization

Citations

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

Fields of papers citing papers by Seishi Ogawa

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Seishi Ogawa

This figure shows the co-authorship network connecting the top 25 collaborators of Seishi Ogawa. A scholar is included among the top collaborators of Seishi Ogawa 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 Seishi Ogawa. Seishi Ogawa 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

Huang, Ying‐Jung, Kazuaki Yokoyama, Ting‐Yu Huang, et al.. (2025). Whole-genome sequencing of myeloproliferative neoplasms revealed dynamic clonal changes in the fibrotic or leukemic transformation and novel FOXP1 mutations in the fibrotic transformation. Leukemia. 39(5). 1218–1227. 2 indexed citations

Miyazaki, Kazuko, Kenta Horie, Hitomi Watanabe, et al.. (2025). A feedback amplifier circuit with Notch and E2A orchestrates T-cell fate and suppresses the innate lymphoid cell lineages during thymic ontogeny. Genes & Development. 39(5-6). 384–400. 1 indexed citations

Guzzi, Nicola, Sowndarya Muthukumar, Maciej Cieśla, et al.. (2022). Pseudouridine-modified tRNA fragments repress aberrant protein synthesis and predict leukaemic progression in myelodysplastic syndrome. Nature Cell Biology. 24(3). 299–306. 78 indexed citations

Takeuchi, Yasuhide, Yohei Mineharu, Yoshiki Arakawa, et al.. (2022). A novel SREBF1::NACC1 gene fusion in an unclassifiable intracranial tumour. Neuropathology and Applied Neurobiology. 48(7). e12843–e12843. 1 indexed citations

Nishimura, Akira, Shinsuke Hirabayashi, Daisuke Hasegawa, et al.. (2020). Acquisition of monosomy 7 and a RUNX1 mutation in Pearson syndrome. Pediatric Blood & Cancer. 68(2). e28799–e28799. 4 indexed citations

Chung, Elaine Y., Urvi A. Shah, Yongqiang Wei, et al.. (2019). PAK Kinase Inhibition Has Therapeutic Activity in Novel Preclinical Models of Adult T-Cell Leukemia/Lymphoma. Clinical Cancer Research. 25(12). 3589–3601. 17 indexed citations

Kon, Ayana, Satoshi Yamazaki, Yasuhito Nannya, et al.. (2017). Physiological Srsf2 P95H expression causes impaired hematopoietic stem cell functions and aberrant RNA splicing in mice. Blood. 131(6). 621–635. 60 indexed citations

Miyazaki, Masaki, Kazuko Miyazaki, Kenian Chen, et al.. (2017). The E-Id Protein Axis Specifies Adaptive Lymphoid Cell Identity and Suppresses Thymic Innate Lymphoid Cell Development. Immunity. 46(5). 818–834.e4. 75 indexed citations

Matsushita, Hirokazu, Yusuke Sato, Takahiro Karasaki, et al.. (2016). Neoantigen Load, Antigen Presentation Machinery, and Immune Signatures Determine Prognosis in Clear Cell Renal Cell Carcinoma. Cancer Immunology Research. 4(5). 463–471. 74 indexed citations

10.

Maeda, Takuya, Seiji Nagano, Hiroshi Ichise, et al.. (2016). Regeneration of CD8αβ T Cells from T-cell–Derived iPSC Imparts Potent Tumor Antigen-Specific Cytotoxicity. Cancer Research. 76(23). 6839–6850. 90 indexed citations

11.

Sato‐Otsubo, Aiko, Yasuhito Nannya, Koichi Kashiwase, et al.. (2015). Genome-wide surveillance of mismatched alleles for graft-versus-host disease in stem cell transplantation. Blood. 126(25). 2752–2763. 21 indexed citations

12.

Dumitriu, Bogdan, Xingmin Feng, Danielle M. Townsley, et al.. (2014). Telomere attrition and candidate gene mutations preceding monosomy 7 in aplastic anemia. Blood. 125(4). 706–709. 58 indexed citations

13.

Nakaya, Takeo, Seishi Ogawa, Ichiro Manabe, et al.. (2014). KLF5 Regulates the Integrity and Oncogenicity of Intestinal Stem Cells. Cancer Research. 74(10). 2882–2891. 57 indexed citations

14.

Matsunawa, Manabu, Ryō Yamamoto, Masashi Sanada, et al.. (2014). Haploinsufficiency of Sf3b1 leads to compromised stem cell function but not to myelodysplasia. Leukemia. 28(9). 1844–1850. 37 indexed citations

15.

Muto, Tomoya, Goro Sashida, Motohiko Oshima, et al.. (2013). Concurrent loss of Ezh2 and Tet2 cooperates in the pathogenesis of myelodysplastic disorders. The Journal of Experimental Medicine. 210(12). 2627–2639. 137 indexed citations

16.

Iwakawa, Reika, Takashi Kohno, Motohiro Kato, et al.. (2010). MYC Amplification as a Prognostic Marker of Early-Stage Lung Adenocarcinoma Identified by Whole Genome Copy Number Analysis. Clinical Cancer Research. 17(6). 1481–1489. 71 indexed citations

17.

Nakahara, Fumio, Mamiko Sakata‐Yanagimoto, Yukiko Komeno, et al.. (2009). Hes1 immortalizes committed progenitors and plays a role in blast crisis transition in chronic myelogenous leukemia. Blood. 115(14). 2872–2881. 54 indexed citations

18.

Hirobe, Tomohisa, et al.. (2009). Mitochondria are more numerous and smaller in pink-eyed dilution melanoblasts than in wild-type melanocytes in the neonatal mouse epidermis. Pigment Cell & Melanoma Research. 22(6). 914. 3 indexed citations

19.

Jacobs, Sharoni, Ella R. Thompson, Yasuhito Nannya, et al.. (2007). Genome-Wide, High-Resolution Detection of Copy Number, Loss of Heterozygosity, and Genotypes from Formalin-Fixed, Paraffin-Embedded Tumor Tissue Using Microarrays. Cancer Research. 67(6). 2544–2551. 65 indexed citations

20.

Nannya, Yasuhito, Masashi Sanada, Kumi Nakazaki, et al.. (2005). A Robust Algorithm for Copy Number Detection Using High-Density Oligonucleotide Single Nucleotide Polymorphism Genotyping Arrays. Cancer Research. 65(14). 6071–6079. 501 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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