M Maruyama

21 papers receiving 464 citations

Peers

M Maruyama
Comparison fields: 5 of 67
  • Virology 51
  • Nephrology 61
  • Rheumatology 100
  • Immunology 87
  • Hepatology 26
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J Bedrossian France
Jean Philippe Bastard France
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Citations per year

Countries citing papers authored by M Maruyama

Since Specialization
Citations

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

Fields of papers citing papers by M Maruyama

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside M Maruyama, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with M Maruyama Line = papers co-authored together M Maruyama links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 21 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Altered levels of adipocytokines in association with insulin resistance in patients with systemic lupus erythematosus.
2006121
2 201194
3 199588
4
Cell-cycle kinetics and VSV-G pseudotyped retrovirus-mediated gene transfer in blood-derived CD34+ cells.
199637
5 200930
6 201523
7 200615
8 200711
9 200811
10 20039
11 19898
12
Mobilization and purification of CD34+ cells from normal donors-regimens with G-CSF, GM-CSF, or a combination of both.
19967
13
Usefulness of Measurement of Visceral Fat Area by Dual Impedance Method and Points for Attention in Interpretation of Results - From Viewpoint of Diagnosis of Metabolic Syndrome and Early-stage Atherosclerosis-
20126
14 20035
15 20034
16 20034
17 20034
18 20032
19
[Epidemiology of IDDM].
19972
20 20031

About M Maruyama

M Maruyama is a scholar working on Molecular Biology, Genetics, Surgery, Hepatology and Nephrology, having authored 21 papers that have together received 483 indexed citations. Recurring topics across this work include Liver physiology and pathology (5 papers), Virus-based gene therapy research (5 papers), RNA Interference and Gene Delivery (4 papers), Pancreatic function and diabetes (4 papers), Renal Diseases and Glomerulopathies (3 papers), Systemic Lupus Erythematosus Research (3 papers), Hematopoietic Stem Cell Transplantation (2 papers) and Vitamin C and Antioxidants Research (1 paper). The work is most often cited by research in Virology (51 citations), Nephrology (61 citations), Rheumatology (100 citations), Immunology (87 citations) and Hepatology (26 citations). M Maruyama has collaborated with scholars based in Japan and United States. Frequent co-authors include Yohei Maeshima, Hirofumi Makino, Hitoshi Sugiyama, Ken‐ei Sada, Toshiki Fukui, Kazuhiro Yamauchi, Tadashi Yasuda, Youichi Abe, D.J. Young and Masahiro Yamamura. Their work appears in journals such as Clinical Nephrology, Diabetes Research and Clinical Practice, Clinical Therapeutics, Proceedings of the National Academy of Sciences and The Journal of Rheumatology.

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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