Takashi Hiroyama

2.1k total citations
32 papers, 1.6k citations indexed

About

Takashi Hiroyama is a scholar working on Immunology, Molecular Biology and Physiology. According to data from OpenAlex, Takashi Hiroyama has authored 32 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Immunology, 11 papers in Molecular Biology and 11 papers in Physiology. Recurrent topics in Takashi Hiroyama's work include Erythrocyte Function and Pathophysiology (10 papers), Pluripotent Stem Cells Research (7 papers) and Mesenchymal stem cell research (6 papers). Takashi Hiroyama is often cited by papers focused on Erythrocyte Function and Pathophysiology (10 papers), Pluripotent Stem Cells Research (7 papers) and Mesenchymal stem cell research (6 papers). Takashi Hiroyama collaborates with scholars based in Japan, United States and Australia. Takashi Hiroyama's co-authors include Yukio Nakamura, Kenichi Miharada, Kazuhiro Sudo, Toshiro Nagasawa, Hiromitsu Nakauchi, Ryo Kurita, Kenzaburo Tani, Hiroyuki Miyoshi, Naoya Takayama and Hiroko Tsukui and has published in prestigious journals such as Journal of Biological Chemistry, SHILAP Revista de lepidopterología and Blood.

In The Last Decade

Takashi Hiroyama

32 papers receiving 1.5k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Takashi Hiroyama Japan 14 639 398 381 378 366 32 1.6k
Sachiko Miyagawa Japan 26 514 0.8× 377 0.9× 158 0.4× 168 0.4× 248 0.7× 122 1.9k
Stephen Fitter Australia 24 709 1.1× 201 0.5× 644 1.7× 99 0.3× 317 0.9× 39 1.8k
Marc L. Turner United Kingdom 24 537 0.8× 571 1.4× 410 1.1× 129 0.3× 191 0.5× 54 1.6k
T. Yoshino Japan 23 384 0.6× 895 2.2× 171 0.4× 356 0.9× 195 0.5× 98 2.2k
Simin Saffaripour United States 15 385 0.6× 558 1.4× 937 2.5× 88 0.2× 157 0.4× 17 1.9k
Martin Hafner Germany 13 643 1.0× 786 2.0× 168 0.4× 120 0.3× 103 0.3× 17 1.8k
Chozhavendan Rathinam United States 16 694 1.1× 1.0k 2.6× 390 1.0× 307 0.8× 198 0.5× 23 2.0k
Ralph Giorno United States 24 374 0.6× 924 2.3× 122 0.3× 254 0.7× 113 0.3× 54 2.0k
Aleksandra Wodnar‐Filipowicz Switzerland 23 430 0.7× 1.2k 3.0× 558 1.5× 175 0.5× 247 0.7× 36 2.0k
Hideyuki Matsuzawa Japan 14 551 0.9× 251 0.6× 241 0.6× 89 0.2× 291 0.8× 22 1.1k

Countries citing papers authored by Takashi Hiroyama

Since Specialization
Citations

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

Fields of papers citing papers by Takashi Hiroyama

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Takashi Hiroyama

This figure shows the co-authorship network connecting the top 25 collaborators of Takashi Hiroyama. A scholar is included among the top collaborators of Takashi Hiroyama 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 Takashi Hiroyama. Takashi Hiroyama 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.
Sudo, Kazuhiro, Takeshi Yamada, Takashi Hiroyama, et al.. (2023). Identification of a gene set that maintains tumorigenicity of the hepatocellular carcinoma cell line Li-7. Human Cell. 36(6). 2074–2086. 2 indexed citations
2.
Yamada, Takeshi, Takashi Hiroyama, Kazuhiro Sudo, et al.. (2019). A robust culture method for maintaining tumorigenic cancer stem cells in the hepatocellular carcinoma cell line Li‐7. Cancer Science. 110(5). 1644–1652. 2 indexed citations
3.
Kanemaru, Kazumasa, Emiko Noguchi, Takahiro Tokunaga, et al.. (2015). Tie2 Signaling Enhances Mast Cell Progenitor Adhesion to Vascular Cell Adhesion Molecule-1 (VCAM-1) through α4β1 Integrin. PLoS ONE. 10(12). e0144436–e0144436. 9 indexed citations
4.
Kurita, Ryo, Kazuhiro Sudo, Kenichi Miharada, et al.. (2013). Establishment of Immortalized Human Erythroid Progenitor Cell Lines Able to Produce Enucleated Red Blood Cells. PLoS ONE. 8(3). e59890–e59890. 273 indexed citations
5.
Danjoh, Inaho, et al.. (2012). Dominant Expansion of a Cryptic Subclone with an Abnormal Karyotype in B Lymphoblastoid Cell Lines during Culture. Cytogenetic and Genome Research. 139(2). 88–96. 5 indexed citations
6.
Danjoh, Inaho, Kaoru Saijo, Takashi Hiroyama, & Yukio Nakamura. (2011). The Sonoda–Tajima Cell Collection: A Human Genetics Research Resource with Emphasis on South American Indigenous Populations. Genome Biology and Evolution. 3. 272–283. 6 indexed citations
7.
Nakamura, Yukio, Takashi Hiroyama, Kenichi Miharada, & Ryo Kurita. (2010). Red blood cell production from immortalized progenitor cell line. International Journal of Hematology. 93(1). 5–9. 13 indexed citations
8.
Danjoh, Inaho, et al.. (2009). Is parainfluenza virus a threatening virus for human cancer cell lines?. Human Cell. 22(3). 81–84. 2 indexed citations
9.
Miharada, Kenichi, et al.. (2007). Lipocalin 2‐mediated growth suppression is evident in human erythroid and monocyte/macrophage lineage cells. Journal of Cellular Physiology. 215(2). 526–537. 65 indexed citations
10.
Hiroyama, Takashi, Kazuhiro Sudo, Naoko Aoki, et al.. (2007). Human umbilical cord‐derived cells can often serve as feeder cells to maintain primate embryonic stem cells in a state capable of producing hematopoietic cells. Cell Biology International. 32(1). 1–7. 7 indexed citations
11.
12.
Miharada, Kenichi, Takashi Hiroyama, Kazuhiro Sudo, Toshiro Nagasawa, & Yukio Nakamura. (2006). Efficient enucleation of erythroblasts differentiated in vitro from hematopoietic stem and progenitor cells. Nature Biotechnology. 24(10). 1255–1256. 147 indexed citations
13.
Miharada, Kenichi, Takashi Hiroyama, Kazuhiro Sudo, Toshiro Nagasawa, & Yukio Nakamura. (2006). Refinement of cytokine use in the in vitro expansion of erythroid cells. Human Cell. 19(1). 30–37. 6 indexed citations
14.
Miharada, Kenichi, Takashi Hiroyama, Kazuhiro Sudo, Toshiro Nagasawa, & Yukio Nakamura. (2005). Lipocalin 2 functions as a negative regulator of red blood cell production in an autocrine fashion. The FASEB Journal. 19(13). 1881–1883. 65 indexed citations
15.
16.
Hiroyama, Takashi, Atsushi Iwama, Yukio Nakamura, & Hiromitsu Nakauchi. (2001). Fractalkine Shares Signal Sequence with TARC: Gene Structures and Expression Profiles of Two Chemokine Genes. Genomics. 75(1-3). 3–5. 7 indexed citations
17.
Motohashi, Tsutomu, Yukio Nakamura, Mitsujiro Osawa, et al.. (2001). Increased cell surface expression of C‐terminal truncated erythropoietin receptors in polycythemia. European Journal Of Haematology. 67(2). 88–93. 14 indexed citations
18.
Hiroyama, Takashi, Atsushi Iwama, Yohei Morita, et al.. (2000). Molecular Cloning and Characterization of CRLM-2, a Novel Type I Cytokine Receptor Preferentially Expressed in Hematopoietic Cells. Biochemical and Biophysical Research Communications. 272(1). 224–229. 28 indexed citations
19.
Shibuya, Akira, Norihisa Sakamoto, Yoshio Shimizu, et al.. (2000). Fcα/μ receptor mediates endocytosis of IgM-coated microbes. Nature Immunology. 1(5). 441–446. 300 indexed citations
20.
Nakamura, Yukio, Hiroki Takano, Masatake Osawa, et al.. (1998). Impaired erythropoiesis in transgenic mice overexpressing a truncated erythropoietin receptor.. PubMed. 26(12). 1105–10. 13 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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