Hajime Hiraragi

919 total citations
17 papers, 647 citations indexed

About

Hajime Hiraragi is a scholar working on Immunology, Ecology, Evolution, Behavior and Systematics and Agronomy and Crop Science. According to data from OpenAlex, Hajime Hiraragi has authored 17 papers receiving a total of 647 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Immunology, 6 papers in Ecology, Evolution, Behavior and Systematics and 5 papers in Agronomy and Crop Science. Recurrent topics in Hajime Hiraragi's work include T-cell and Retrovirus Studies (8 papers), Animal Disease Management and Epidemiology (5 papers) and Vector-Borne Animal Diseases (5 papers). Hajime Hiraragi is often cited by papers focused on T-cell and Retrovirus Studies (8 papers), Animal Disease Management and Epidemiology (5 papers) and Vector-Borne Animal Diseases (5 papers). Hajime Hiraragi collaborates with scholars based in United States, Italy and China. Hajime Hiraragi's co-authors include Michael D. Lairmore, Vincenzo Ciminale, Micol Silic‐Benussi, Bindhu Michael, Lee Ratner, Donna M. D’Agostino, Helga Raab, Mark X. Sliwkowski, Debra L. Dugger and Guangmin Li and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Cancer Research and Journal of Virology.

In The Last Decade

Hajime Hiraragi

16 papers receiving 621 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Hajime Hiraragi United States 13 284 202 192 190 188 17 647
Naomi Taylor France 8 508 1.8× 197 1.0× 15 0.1× 182 1.0× 151 0.8× 16 827
Brandon J. Lamarche United States 10 68 0.2× 68 0.3× 16 0.1× 34 0.2× 176 0.9× 15 679
Bonnie Landmeier United States 9 155 0.5× 25 0.1× 217 1.1× 8 0.0× 143 0.8× 11 593
Fabian Vandermeers Belgium 9 359 1.3× 272 1.3× 5 0.0× 215 1.1× 117 0.6× 14 645
Isolde Pfeuffer Germany 9 341 1.2× 19 0.1× 15 0.1× 18 0.1× 179 1.0× 9 719
Josef Bodor United States 14 375 1.3× 27 0.1× 9 0.0× 22 0.1× 99 0.5× 22 669
Sayaka Ito Japan 15 268 0.9× 30 0.1× 11 0.1× 32 0.2× 34 0.2× 25 623
P Kontsek Slovakia 14 298 1.0× 16 0.1× 186 1.0× 4 0.0× 126 0.7× 56 566
Hajime Kamijuku Japan 9 195 0.7× 32 0.2× 44 0.2× 28 0.1× 53 0.3× 9 374
Kavita Mistry United States 10 512 1.8× 21 0.1× 40 0.2× 15 0.1× 33 0.2× 27 840

Countries citing papers authored by Hajime Hiraragi

Since Specialization
Citations

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

Fields of papers citing papers by Hajime Hiraragi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hajime Hiraragi

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

All Works

17 of 17 papers shown
1.
Li, Aileen W., Jessica Briones, Jia Lü, et al.. (2024). Engineering potent chimeric antigen receptor T cells by programming signaling during T-cell activation. Scientific Reports. 14(1). 21331–21331. 3 indexed citations
2.
Zhang, Jun, Alan Knapton, Steven E. Lipshultz, et al.. (2013). Sex-related Differences in Mast Cell Activity and Doxorubicin Toxicity. Toxicologic Pathology. 42(2). 361–375. 45 indexed citations
3.
Lin, Kedan, Crystal Zhang, Eric B. Harstad, et al.. (2013). Abstract 5619: Preclinical development of anti-SLC34A2 antibody drug conjugate as a therapeutic for non-small cell lung and ovarian cancers.. Cancer Research. 73(8_Supplement). 5619–5619.
4.
Diaz, Dolores, Krishna P. Allamneni, Jacqueline M. Tarrant, et al.. (2011). Phosphorous Dysregulation Induced by MEK Small Molecule Inhibitors in the Rat Involves Blockade of FGF-23 Signaling in the Kidney. Toxicological Sciences. 125(1). 187–195. 15 indexed citations
5.
Junutula, Jagath R., Kelly M. Flagella, Richard Graham, et al.. (2010). Engineered Thio-Trastuzumab-DM1 Conjugate with an Improved Therapeutic Index to Target Human Epidermal Growth Factor Receptor 2–Positive Breast Cancer. Clinical Cancer Research. 16(19). 4769–4778. 214 indexed citations
6.
Herman, Eugene H., Alan Knapton, Jun Zhang, Hajime Hiraragi, & Steven E. Lipshultz. (2008). Gender is a factor that can impact the severity of doxorubicin (DXR) toxicity in spontaneously hypertensive rats (SHR). The FASEB Journal. 22(S1). 4 indexed citations
7.
Datta, Antara, Lee Silverman, Andrew J. Phipps, et al.. (2007). Human T-lymphotropic virus type-1 p30 alters cell cycle G2 regulation of T lymphocytes to enhance cell survival. Retrovirology. 4(1). 49–49. 28 indexed citations
9.
Hiraragi, Hajime, Seung-Jae Kim, Andrew J. Phipps, et al.. (2006). Human T-Lymphotropic Virus Type 1 Mitochondrion-Localizing Protein p13 II Is Required for Viral Infectivity In Vivo. Journal of Virology. 80(7). 3469–3476. 48 indexed citations
10.
Michael, Bindhu, Hajime Hiraragi, Soledad Fernández, et al.. (2005). Human T Lymphotropic Virus Type 1 Accessory Protein p12 I Modulates Calcium-Mediated Cellular Gene Expression and Enhances p300 Expression in T Lymphocytes. AIDS Research and Human Retroviruses. 21(4). 273–284. 14 indexed citations
11.
D’Agostino, Donna M., Micol Silic‐Benussi, Hajime Hiraragi, Michael D. Lairmore, & Vincenzo Ciminale. (2005). The human T-cell leukemia virus type 1 p13II protein: effects on mitochondrial function and cell growth. Cell Death and Differentiation. 12(S1). 905–915. 37 indexed citations
12.
Hiraragi, Hajime, et al.. (2005). Human T-Lymphotropic Virus Type 1 Mitochondrion-Localizing Protein p13 II Sensitizes Jurkat T Cells to Ras-Mediated Apoptosis. Journal of Virology. 79(15). 9449–9457. 37 indexed citations
13.
Michael, Bindhu, Hajime Hiraragi, Lei Shen, et al.. (2004). Human T lymphotropic virus type-1 p30II alters cellular gene expression to selectively enhance signaling pathways that activate T lymphocytes. Retrovirology. 1(1). 39–39. 39 indexed citations
14.
Silic‐Benussi, Micol, Ilaria Cavallari, Elisabetta Rossi, et al.. (2004). Suppression of tumor growth and cell proliferation by p13 II , a mitochondrial protein of human T cell leukemia virus type 1. Proceedings of the National Academy of Sciences. 101(17). 6629–6634. 60 indexed citations
15.
O’Rourke, John P., et al.. (2003). Analysis of gene transfer and expression in skeletal muscle using enhanced EIAV lentivirus vectors. Molecular Therapy. 7(5). 632–639. 29 indexed citations
16.
Valberg, Stephanie J., Bonnie R. Rush, Hailu Kinde, et al.. (2001). Glycogen Branching Enzyme Deficiency in Quarter Horse Foals. Journal of Veterinary Internal Medicine. 15(6). 572–572. 9 indexed citations
17.
Valberg, Stephanie J., Bonnie R. Rush, Hailu Kinde, et al.. (2001). Glycogen Branching Enzyme Deficiency in Quarter Horse Foals. Journal of Veterinary Internal Medicine. 15(6). 572–580. 46 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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