M Teramura

629 total citations
11 papers, 516 citations indexed

About

M Teramura is a scholar working on Hematology, Genetics and Immunology. According to data from OpenAlex, M Teramura has authored 11 papers receiving a total of 516 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Hematology, 6 papers in Genetics and 6 papers in Immunology. Recurrent topics in M Teramura's work include Chronic Lymphocytic Leukemia Research (5 papers), Platelet Disorders and Treatments (5 papers) and Lymphoma Diagnosis and Treatment (4 papers). M Teramura is often cited by papers focused on Chronic Lymphocytic Leukemia Research (5 papers), Platelet Disorders and Treatments (5 papers) and Lymphoma Diagnosis and Treatment (4 papers). M Teramura collaborates with scholars based in Japan and Pakistan. M Teramura's co-authors include Kazuo Oshimi, Hideaki Mizoguchi, Shigeru Hoshino, Isamu Sugawara, Ryukichi Ryo, Hironori Nakajima, Mitsuoki Eguchi, Yasuhide Hayashi, Takeyuki Sato and Akira Fuse and has published in prestigious journals such as Blood, British Journal of Haematology and Leukemia Research.

In The Last Decade

M Teramura

11 papers receiving 498 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
M Teramura Japan 9 288 167 163 136 116 11 516
F W Jacobsen Norway 8 208 0.7× 207 1.2× 247 1.5× 83 0.6× 113 1.0× 9 547
Colvin Om United States 9 190 0.7× 169 1.0× 63 0.4× 122 0.9× 84 0.7× 11 428
J A Katzmann United States 9 298 1.0× 156 0.9× 72 0.4× 86 0.6× 153 1.3× 20 592
Nel R. Blom Netherlands 11 405 1.4× 130 0.8× 96 0.6× 122 0.9× 52 0.4× 22 600
E. Wunder France 11 332 1.2× 147 0.9× 121 0.7× 98 0.7× 306 2.6× 28 696
N Aoki Japan 10 233 0.8× 173 1.0× 84 0.5× 84 0.6× 85 0.7× 12 446
A. Kabral Australia 13 443 1.5× 119 0.7× 132 0.8× 76 0.6× 73 0.6× 26 610
Alexander Ws Australia 7 425 1.5× 138 0.8× 145 0.9× 155 1.1× 126 1.1× 9 637
J. Graham Sharp United States 12 255 0.9× 181 1.1× 113 0.7× 96 0.7× 250 2.2× 26 633
A Severino Italy 13 297 1.0× 117 0.7× 104 0.6× 131 1.0× 98 0.8× 16 429

Countries citing papers authored by M Teramura

Since Specialization
Citations

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

Fields of papers citing papers by M Teramura

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of M Teramura

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

All Works

11 of 11 papers shown
2.
Kobayashi, Shoko, et al.. (1993). Circulating megakaryocyte progenitors in myeloproliferative disorders are hypersensitive to interleukin‐3. British Journal of Haematology. 83(4). 539–544. 39 indexed citations
3.
Teramura, M, et al.. (1993). Interleukin-11 acts as an autocrine growth factor for human megakaryoblastic cell lines. Blood. 81(4). 889–893. 1 indexed citations
4.
Kaneko, Tatsuo, M Masuda, M Teramura, et al.. (1993). A bispecific antibody enhances cytokine-induced killer-mediated cytolysis of autologous acute myeloid leukemia cells. Blood. 81(5). 1333–1341. 1 indexed citations
5.
Kaneko, Tatsuo, M Masuda, M Teramura, et al.. (1993). A bispecific antibody enhances cytokine-induced killer-mediated cytolysis of autologous acute myeloid leukemia cells. Blood. 81(5). 1333–1341. 28 indexed citations
6.
Teramura, M, et al.. (1993). Interleukin-11 acts as an autocrine growth factor for human megakaryoblastic cell lines. Blood. 81(4). 889–893. 74 indexed citations
7.
Teramura, M, et al.. (1992). Stimulatory effect of tumor necrosis factor-α on the growth of CMK, a human megakaryoblastic leukemia cell line. Leukemia Research. 16(3). 281–285. 11 indexed citations
8.
Teramura, M, et al.. (1992). Interleukin-11 enhances human megakaryocytopoiesis in vitro. Blood. 79(2). 327–331. 163 indexed citations
9.
Hoshino, Shigeru, Kazuo Oshimi, M Teramura, & Hiroyuki Mizoguchi. (1991). Activation via the CD3 and CD16 pathway mediates interleukin-2- dependent autocrine proliferation of granular lymphocytes in patients with granular lymphocyte proliferative disorders. Blood. 78(12). 3232–3240. 11 indexed citations
10.
Hoshino, Shigeru, Kazuo Oshimi, Mitsuru Tsudo, et al.. (1990). Flow cytometric analysis of expression of interleukin-2 receptor beta chain (p70-75) on various leukemic cells. Blood. 76(4). 767–774. 30 indexed citations
11.
Sato, Takeyuki, Akira Fuse, Mitsuoki Eguchi, et al.. (1989). Establishment of a human leukaemic cell line (CMK) with megakaryocytic characteristics from a Down's syndrome patient with acute megakaryoblastic leukaemia. British Journal of Haematology. 72(2). 184–190. 149 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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