Taro Maruyama

4.2k total citations
124 papers, 3.2k citations indexed

About

Taro Maruyama is a scholar working on Genetics, Endocrinology, Diabetes and Metabolism and Surgery. According to data from OpenAlex, Taro Maruyama has authored 124 papers receiving a total of 3.2k indexed citations (citations by other indexed papers that have themselves been cited), including 80 papers in Genetics, 62 papers in Endocrinology, Diabetes and Metabolism and 54 papers in Surgery. Recurrent topics in Taro Maruyama's work include Diabetes and associated disorders (75 papers), Pancreatic function and diabetes (51 papers) and Diabetes Management and Research (45 papers). Taro Maruyama is often cited by papers focused on Diabetes and associated disorders (75 papers), Pancreatic function and diabetes (51 papers) and Diabetes Management and Research (45 papers). Taro Maruyama collaborates with scholars based in Japan, United States and Sweden. Taro Maruyama's co-authors include Akira Shimada, Tetsuro Kobayashi, Akira Kasuga, Eiji Kawasaki, Takuya Awata, Shoichiro Tanaka, Takao Saruta, Izumi Takei, Hiroshi Ikegami and Yumiko Kawabata and has published in prestigious journals such as Blood, PLoS ONE and The Journal of Clinical Endocrinology & Metabolism.

In The Last Decade

Taro Maruyama

122 papers receiving 3.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Taro Maruyama Japan 32 1.9k 1.4k 1.3k 594 495 124 3.2k
Leentje Van Lommel Belgium 35 1.3k 0.7× 546 0.4× 1.3k 1.0× 880 1.5× 1.1k 2.3× 57 3.8k
Michal Procházka United States 32 1.6k 0.8× 675 0.5× 1.2k 0.9× 786 1.3× 1.7k 3.4× 76 4.2k
Holger Luthman Sweden 34 1.5k 0.8× 1.4k 1.0× 798 0.6× 554 0.9× 2.7k 5.5× 111 4.8k
Abdelaziz Amrani Canada 30 1.2k 0.6× 450 0.3× 680 0.5× 1.7k 2.8× 496 1.0× 53 2.9k
Masataka Kudo Japan 40 521 0.3× 1.0k 0.8× 1.1k 0.8× 221 0.4× 1.8k 3.7× 128 4.9k
Jadwiga Furmaniak United Kingdom 39 1.3k 0.7× 3.4k 2.5× 416 0.3× 527 0.9× 1.1k 2.2× 131 4.8k
Anne Bachelot France 36 974 0.5× 1.6k 1.1× 368 0.3× 278 0.5× 1.5k 3.1× 132 4.0k
Mark Lathrop France 28 1.4k 0.7× 319 0.2× 383 0.3× 456 0.8× 1.3k 2.5× 48 3.4k
Thomas Bouckenooghe Belgium 17 645 0.3× 436 0.3× 811 0.6× 242 0.4× 502 1.0× 28 1.9k
Elizabeth Smith United States 23 721 0.4× 863 0.6× 222 0.2× 312 0.5× 847 1.7× 42 3.2k

Countries citing papers authored by Taro Maruyama

Since Specialization
Citations

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

Fields of papers citing papers by Taro Maruyama

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Taro Maruyama

This figure shows the co-authorship network connecting the top 25 collaborators of Taro Maruyama. A scholar is included among the top collaborators of Taro Maruyama 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 Taro Maruyama. Taro Maruyama 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.
2.
Hirata, Takumi, Masafumi Koga, Soji Kasayama, Jiro Morimoto, & Taro Maruyama. (2014). Glycated albumin is not significantly correlated with body mass index in patients with acute-onset type 1 diabetes. Clinica Chimica Acta. 438. 248–251. 5 indexed citations
3.
Maruyama, Taro, Terumichi Nakagawa, Akira Kasuga, & Mitsuru Murata. (2011). Heterogeneity among patients with latent autoimmune diabetes in adults. Diabetes/Metabolism Research and Reviews. 27(8). 971–974. 14 indexed citations
4.
Maruyama, Taro, et al.. (2009). MCP-1 gene A-2518G polymorphism and carotid artery atherosclerosis in patients with type 2 diabetes. Diabetes Research and Clinical Practice. 86(3). 193–198. 25 indexed citations
5.
Tanaka, Shoichiro, Yoriko Nishida, Kaoru Aida, et al.. (2009). Enterovirus Infection, CXC Chemokine Ligand 10 (CXCL10), and CXCR3 Circuit. Diabetes. 58(10). 2285–2291. 124 indexed citations
6.
7.
MURASE, Yoshio, Akihisa Imagawa, Toshiaki Hanafusa, et al.. (2007). Fulminant type 1 diabetes as a high risk group for diabetic microangiopathy—a nationwide 5-year-study in Japan. Diabetologia. 50(3). 531–537. 27 indexed citations
8.
Murayama, Hiroshi, Nobuo Matsuura, Tomoyuki Kawamura, et al.. (2006). A sensitive radioimmunoassay of insulin autoantibody: Reduction of non-specific binding of [125I]insulin. Journal of Autoimmunity. 26(2). 127–132. 23 indexed citations
9.
Imagawa, Akihisa, Toshiaki Hanafusa, Yasuko Uchigata, et al.. (2005). Different contribution of class II HLA in fulminant and typical autoimmune type 1 diabetes mellitus. Diabetologia. 48(2). 294–300. 92 indexed citations
10.
Saisho, Yoshifumi, et al.. (2005). Effect of switching from NPH insulin to insulin glargine on glycemic control in Japanese type 1 diabetic patients. 48(9). 685–691. 2 indexed citations
11.
Nakano, Takanari, et al.. (2003). NAD(P)H oxidase p22phox Gene C242T polymorphism and lipoprotein oxidation. Clinica Chimica Acta. 335(1-2). 101–107. 16 indexed citations
12.
Nakanishi, Mamoru, Yoshikazu Takanami, Taro Maruyama, et al.. (2003). The Ratio of Serum Paraoxonase/Arylesterase Activity Using an Improved Assay for Arylesterase Activity to Discriminate PON1R192 from PON1Q192. Journal of Atherosclerosis and Thrombosis. 10(6). 337–342. 33 indexed citations
13.
Oikawa, Yoichi, Akira Shimada, Satoru Yamada, et al.. (2003). NKT Cell Frequency in Japanese Type 1 Diabetes. Annals of the New York Academy of Sciences. 1005(1). 230–232. 11 indexed citations
14.
Shimada, Akira, Keiichi Kodama, Jiro Morimoto, et al.. (2003). Detection of GAD‐Reactive CD4+ Cells in So‐Called “Type 1B” Diabetes. Annals of the New York Academy of Sciences. 1005(1). 378–386. 6 indexed citations
15.
Yamada, Satoru, Yoshiko Motohashi, Tatsuo Yanagawa, et al.. (2001). NeuroD/BETA2 Gene G→A Polymorphism May Affect Onset Pattern of Type 1 Diabetes in Japanese. Diabetes Care. 24(8). 1438–1441. 22 indexed citations
16.
Murakami, Yasufumi, Hiroshi Uejima, Hiroshi Fukuhara, et al.. (2000). Construction of human–rodent hybrid cells containing single transferable fragments of human chromosome 10p. Journal of Human Genetics. 45(6). 370–373. 4 indexed citations
17.
Maruyama, Taro, Akira Shimada, Akira Kasuga, et al.. (1994). Analysis of MHC Class II antigens in Japanese IDDM by a novel HLA-typing method, hybridization protection assay. Diabetes Research and Clinical Practice. 23(2). 77–84. 21 indexed citations
18.
Falorni, Alberto, C. E. Grubin, Izumi Takei, et al.. (1994). Radioimmunoassay Detects the Frequent Occurrence of Autoantibodies to the Mr 65,000 Isoform of Glutamic Acid Decarboxylase in Japanese Insulin-Dependent Diabetes. Autoimmunity. 19(2). 113–125. 59 indexed citations
19.
Tanaka, Naohiko, et al.. (1992). A Case of Insulin-Dependent Diabetes Mellitus Developing After Elevation of Serum Amylase Level and Low Plasma Glucose Level. 35(2). 121–126. 2 indexed citations
20.
Nakamura, Masahiko, et al.. (1989). A Case of Legionnaires' Disease Associated with Rhabdomyolysis. Kansenshogaku zasshi. 63(1). 79–82. 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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