Tomoko Matsumoto

8.8k total citations · 1 hit paper
280 papers, 6.7k citations indexed

About

Tomoko Matsumoto is a scholar working on Hematology, Surgery and Molecular Biology. According to data from OpenAlex, Tomoko Matsumoto has authored 280 papers receiving a total of 6.7k indexed citations (citations by other indexed papers that have themselves been cited), including 62 papers in Hematology, 47 papers in Surgery and 44 papers in Molecular Biology. Recurrent topics in Tomoko Matsumoto's work include Hemophilia Treatment and Research (40 papers), Blood Coagulation and Thrombosis Mechanisms (33 papers) and Platelet Disorders and Treatments (25 papers). Tomoko Matsumoto is often cited by papers focused on Hemophilia Treatment and Research (40 papers), Blood Coagulation and Thrombosis Mechanisms (33 papers) and Platelet Disorders and Treatments (25 papers). Tomoko Matsumoto collaborates with scholars based in Japan, United States and United Kingdom. Tomoko Matsumoto's co-authors include Yorio Hinuma, S Shirakawa, Keiko Nagata, I Miyoshi, Masao Hanaoka, Michikazu Nakai, Midori Shima, Keiji Nogami, Hiroyuki Shindo and Kenichi Ogiwara and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and Journal of Biological Chemistry.

In The Last Decade

Tomoko Matsumoto

254 papers receiving 6.4k citations

Hit Papers

Adult T-cell leukemia: antigen in an ATL cell line and de... 1981 2026 1996 2011 1981 500 1000 1.5k
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.

  1. Adult T-cell leukemia: antigen in an ATL cell line and detection of antibodies to the antigen in human sera.
    1981 1.9k citations Tomoko Matsumoto et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Tomoko Matsumoto Japan 37 2.1k 1.6k 1.5k 1.3k 1.1k 280 6.7k
Kusuki Nishioka Japan 43 1.6k 0.8× 382 0.2× 324 0.2× 1.7k 1.3× 196 0.2× 212 5.6k
Houshang Rafatpanah Iran 32 1.4k 0.6× 617 0.4× 498 0.3× 878 0.7× 132 0.1× 204 3.4k
Thomas J. Rosol United States 47 913 0.4× 273 0.2× 150 0.1× 3.6k 2.7× 139 0.1× 286 8.6k
Makoto Matsui Japan 33 2.3k 1.1× 121 0.1× 123 0.1× 3.9k 3.0× 179 0.2× 151 12.3k
Geoffrey W. Tregear Australia 50 355 0.2× 116 0.1× 260 0.2× 3.6k 2.7× 151 0.1× 205 10.2k
Jan J. Brosens United Kingdom 71 9.9k 4.6× 705 0.4× 26 0.0× 3.8k 2.9× 443 0.4× 252 17.2k
Lois A. Salamonsen Australia 67 8.8k 4.1× 1.4k 0.9× 19 0.0× 2.7k 2.1× 761 0.7× 271 14.1k
Robert Pijnenborg Belgium 43 4.4k 2.0× 124 0.1× 34 0.0× 1.4k 1.1× 421 0.4× 139 12.0k
Kanji Sato Japan 38 542 0.3× 106 0.1× 72 0.0× 1.4k 1.1× 115 0.1× 138 4.0k
Maciej Kurpisz Poland 40 1.0k 0.5× 230 0.1× 32 0.0× 1.8k 1.3× 69 0.1× 252 6.1k

Countries citing papers authored by Tomoko Matsumoto

Since Specialization
Citations

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

Fields of papers citing papers by Tomoko Matsumoto

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tomoko Matsumoto

This figure shows the co-authorship network connecting the top 25 collaborators of Tomoko Matsumoto. A scholar is included among the top collaborators of Tomoko Matsumoto 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 Tomoko Matsumoto. Tomoko Matsumoto 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.
Matsumoto, Tomoko, Takayuki Kondo, Kayoko Tsukita, et al.. (2024). Enrichment of Allelic Editing Outcomes by Prime Editing in Induced Pluripotent Stem Cells. The CRISPR Journal. 7(5). 293–304. 2 indexed citations
2.
Matsumoto, Tomoko & Noriko Inada. (2024). Functions of actin and myosin in the nucleus. CYTOLOGIA. 89(4). 263–269.
3.
4.
Matsumoto, Tomoko, et al.. (2023). Surgical Treatment Outcomes for Idiopathic Chronic Megacolon and Megarectum. Nihon Daicho Komonbyo Gakkai Zasshi. 76(8). 509–515.
5.
Sakai, Kouji, Mandy Siu Yu Lung, Tomoko Matsumoto, et al.. (2023). ACE2 knockout hinders SARS-CoV-2 propagation in iPS cell-derived airway and alveolar epithelial cells. Frontiers in Cell and Developmental Biology. 11. 1290876–1290876. 2 indexed citations
6.
Matsumoto, Tomoko, et al.. (2021). Functional Analysis of Poplar Sombrero-Type NAC Transcription Factors Yields a Strategy to Modify Woody Cell Wall Properties. Plant and Cell Physiology. 62(12). 1963–1974. 11 indexed citations
7.
8.
Yada, Koji, Keiji Nogami, Tomoko Matsumoto, Takehisa Kitazawa, & Midori Shima. (2017). Increasing of Ternary Complex Formation By Predominant Accumulation of Factor (F)X Accompanied By Increase of Fixa Contributes to Enhancement of Clotting Function By Apcc in Combination with Emicizumab. Blood. 130. 3658–3658. 1 indexed citations
9.
10.
Ogiwara, Kenichi, Keiji Nogami, Tomoko Matsumoto, & Midori Shima. (2014). Tissue factor pathway inhibitor in activated prothrombin complex concentrates (aPCC) moderates the effectiveness of therapy in some severe hemophilia A patients with inhibitor. International Journal of Hematology. 99(5). 577–587. 17 indexed citations
11.
Yamashita, Atsushi, Sayaka Moriguchi‐Goto, Chihiro Sugita, et al.. (2010). Inhibition of factor XI reduces thrombus formation in rabbit jugular vein under endothelial denudation and/or blood stasis. Thrombosis Research. 125(5). 464–470. 29 indexed citations
12.
13.
Kato, Shingo, Yuki Saito, Rie Tanaka, et al.. (2003). Differential Prevalence of HIV Type 1 Subtype B and CRF01_AE among Different Sexual Transmission Groups in Tokyo, Japan, as Revealed by Subtype-Specific PCR. AIDS Research and Human Retroviruses. 19(11). 1057–1063. 20 indexed citations
14.
Tsurumoto, Toshiyuki, et al.. (2003). 2 Case Reports of SAPHO Syndrome.. Orthopedics & Traumatology. 52(4). 707–711.
15.
Maeshima, Shinichiro, et al.. (2001). Unilateral spatial neglect associated with chronic subdural haematoma: a case report. Brain Injury. 15(4). 371–376. 2 indexed citations
16.
Harada, Toshihide, et al.. (2001). Evaluation of cardiovascular circadian rhythm in patients with Parkinson's disease. 8(4). 269–274. 1 indexed citations
17.
Matsumoto, Tomoko, Hiroshi Enomoto, Katsuro Takahashi, & Satoru Motokawa. (1998). Decreased levels of IGF binding protein-3 in serum from children with Perthes’ disease. Acta Orthopaedica Scandinavica. 69(2). 125–128. 13 indexed citations
18.
Fukunishi, Isao, et al.. (1997). Avoidance Coping Behaviors and Low Social Support Are Related to Depressive Symptoms in HTV-Positive Patients in Japan. Psychosomatics. 38(2). 113–118. 28 indexed citations
19.
20.
Matsumoto, Tomoko, et al.. (1983). Inhibition of mixed lymphocyte culture reaction by cold cytotoxins.. PubMed. 36(2). 214–8. 1 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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