Yoshiro Maru

6.8k total citations · 2 hit papers
89 papers, 5.4k citations indexed

About

Yoshiro Maru is a scholar working on Molecular Biology, Immunology and Hematology. According to data from OpenAlex, Yoshiro Maru has authored 89 papers receiving a total of 5.4k indexed citations (citations by other indexed papers that have themselves been cited), including 64 papers in Molecular Biology, 22 papers in Immunology and 17 papers in Hematology. Recurrent topics in Yoshiro Maru's work include S100 Proteins and Annexins (15 papers), Angiogenesis and VEGF in Cancer (14 papers) and Chronic Myeloid Leukemia Treatments (13 papers). Yoshiro Maru is often cited by papers focused on S100 Proteins and Annexins (15 papers), Angiogenesis and VEGF in Cancer (14 papers) and Chronic Myeloid Leukemia Treatments (13 papers). Yoshiro Maru collaborates with scholars based in Japan, United States and France. Yoshiro Maru's co-authors include Sachie Hiratsuka, Akira Watanabe, Hiroyuki Aburatani, Owen N. Witte, Masabumi Shibuya, Fumimaro Takaku, Fujiko Tsukahara, Hisamaru Hirai, Junji Nishida and Koichi Hagiwara and has published in prestigious journals such as Nature, Science and Cell.

In The Last Decade

Yoshiro Maru

89 papers receiving 5.2k citations

Hit Papers

Tumour-mediated upregulation of chemoattractants and recr... 2006 2026 2012 2019 2006 2008 250 500 750

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Yoshiro Maru Japan 35 3.3k 1.5k 1.2k 900 670 89 5.4k
Thomas O. Daniel United States 38 4.6k 1.4× 1.4k 0.9× 1.2k 1.0× 758 0.8× 992 1.5× 58 7.2k
Masabumi Shibuya Japan 41 4.6k 1.4× 1.7k 1.1× 990 0.8× 1.2k 1.3× 448 0.7× 77 6.6k
Leigh Coultas Australia 24 4.3k 1.3× 1.3k 0.9× 1.1k 0.9× 876 1.0× 351 0.5× 34 5.9k
Noboru Motoyama Japan 36 5.1k 1.6× 1.8k 1.2× 1.8k 1.5× 1.1k 1.3× 277 0.4× 63 7.6k
Anna‐Karin Olsson Sweden 28 2.7k 0.8× 1.1k 0.7× 1.2k 1.0× 848 0.9× 245 0.4× 65 4.8k
T Sudo Japan 33 2.9k 0.9× 1.1k 0.7× 2.1k 1.7× 517 0.6× 254 0.4× 80 5.6k
W. J. Pledger United States 42 5.0k 1.5× 2.5k 1.7× 735 0.6× 1.0k 1.1× 254 0.4× 114 7.9k
Kurt Bommert Germany 35 3.1k 0.9× 1.8k 1.2× 1.2k 1.0× 1.0k 1.1× 202 0.3× 65 5.1k
Grazia Ambrosini United States 27 4.8k 1.4× 2.2k 1.5× 1.2k 1.0× 743 0.8× 199 0.3× 48 6.8k
Giuseppe Viglietto Italy 48 5.4k 1.6× 2.3k 1.5× 687 0.6× 1.6k 1.7× 277 0.4× 150 8.2k

Countries citing papers authored by Yoshiro Maru

Since Specialization
Citations

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

Fields of papers citing papers by Yoshiro Maru

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yoshiro Maru

This figure shows the co-authorship network connecting the top 25 collaborators of Yoshiro Maru. A scholar is included among the top collaborators of Yoshiro Maru 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 Yoshiro Maru. Yoshiro Maru 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.
Ieguchi, Katsuaki, Masabumi Funakoshi, Taishi Mishima, et al.. (2022). The Sympathetic Nervous System Contributes to the Establishment of Pre-Metastatic Pulmonary Microenvironments. International Journal of Molecular Sciences. 23(18). 10652–10652. 12 indexed citations
2.
Deguchi, Atsuko & Yoshiro Maru. (2022). Inflammation-associated premetastatic niche formation. Inflammation and Regeneration. 42(1). 22–22. 22 indexed citations
3.
Ieguchi, Katsuaki, Takeshi Tomita, Toshifumi Takao, et al.. (2021). Analysis of ADAM12-Mediated Ephrin-A1 Cleavage and Its Biological Functions. International Journal of Molecular Sciences. 22(5). 2480–2480. 14 indexed citations
4.
Tomita, Takeshi, Masayoshi Kato, Taishi Mishima, et al.. (2021). Extracellular mRNA transported to the nucleus exerts translation-independent function. Nature Communications. 12(1). 3655–3655. 13 indexed citations
5.
Ieguchi, Katsuaki & Yoshiro Maru. (2019). Roles of EphA1/A2 and ephrin‐A1 in cancer. Cancer Science. 110(3). 841–848. 49 indexed citations
6.
Maru, Yoshiro. (2019). Premetastasis. Cold Spring Harbor Perspectives in Medicine. 10(11). a036897–a036897. 6 indexed citations
7.
Umeda, Masato, Satoru Funamoto, Yoshiro Saito, et al.. (2017). Pleckstrin homology domain of p210 BCRABL interacts with cardiolipin to regulate its mitochondrial translocation and subsequent mitophagy. Genes to Cells. 23(1). 22–34. 9 indexed citations
8.
Hiratsuka, Sachie, Takeshi Tomita, Akira Watanabe, et al.. (2013). Primary tumours modulate innate immune signalling to create pre-metastatic vascular hyperpermeability foci. Nature Communications. 4(1). 1853–1853. 96 indexed citations
9.
Ieguchi, Katsuaki, et al.. (2013). Ephrin-A1 expression induced by S100A8 is mediated by the toll-like receptor 4. Biochemical and Biophysical Research Communications. 440(4). 623–629. 14 indexed citations
10.
Maru, Yoshiro. (2012). Molecular biology of chronic myeloid leukemia. Cancer Science. 103(9). 1601–1610. 33 indexed citations
11.
Maru, Yoshiro. (2011). Inflammation in tumor progression. Folia Pharmacologica Japonica. 138(4). 155–160. 2 indexed citations
12.
Maru, Yoshiro. (2009). Logical structures extracted from metastasis experiments. Cancer Science. 100(11). 2006–2013. 9 indexed citations
13.
Hiratsuka, Sachie, Akira Watanabe, Yoshiko Sakurai, et al.. (2008). The S100A8–serum amyloid A3–TLR4 paracrine cascade establishes a pre-metastatic phase. Nature Cell Biology. 10(11). 1349–1355. 513 indexed citations breakdown →
14.
Masuda, Junko, et al.. (2008). Fibronectin Type I Repeat Is a Nonactivating Ligand for EphA1 and Inhibits ATF3-dependent Angiogenesis. Journal of Biological Chemistry. 283(19). 13148–13155. 11 indexed citations
15.
Maru, Yoshiro, Takeshi Nishino, & Katsuko Kakinuma. (2005). Expression of Nox genes in rat organs, mouse oocytes, and sea urchin eggs. DNA sequence. 16(2). 83–88. 19 indexed citations
16.
Kobayashi, Satsuki, Emi Ito, Reiko Honma, et al.. (2004). Dynamic regulation of gene expression by the Flt-1 kinase and Matrigel in endothelial tubulogenesis. Genomics. 84(1). 185–192. 15 indexed citations
17.
Shimizu, Hiroko, et al.. (2002). Arg tyrosine kinase is involved in homologous recombinational DNA repair. Kanazawa University Repository for Academic Resources (DSpace) (Kanazawa University). 14 indexed citations
18.
Maru, Yoshiro. (2001). Molecular Biology of Chronic Myeloid Leukemia. International Journal of Hematology. 73(3). 308–322. 35 indexed citations
19.
Maru, Yoshiro, Steven K. Hanks, & Masabumi Shibuya. (2001). The tubulogenic activity associated with an activated form of Flt-1 kinase is dependent on focal adhesion kinase. Biochimica et Biophysica Acta (BBA) - Molecular Cell Research. 1540(2). 147–153. 14 indexed citations
20.
Maru, Yoshiro, Daniel Afar, Owen N. Witte, & Masabumi Shibuya. (1996). The Dimerization Property of Glutathione -Transferase Partially Reactivates Bcr-Abl Lacking the Oligomerization Domain. Journal of Biological Chemistry. 271(26). 15353–15357. 78 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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