M Maruyama
- Co-authors
- Yohei MaeshimaKen‐ei SadaHirofumi MakinoHitoshi SugiyamaKazuhiro YamauchiToshiki FukuiTadashi YasudaYouichi Abe
- Topics
- Virus-based gene therapy research (5 papers)Liver physiology and pathology (5 papers)RNA Interference and Gene Delivery (4 papers)
- Cited by
- VirologyNephrologyRheumatology
- Journals
- Proceedings of the National Academy of SciencesDiabetes Research and Clinical PracticeClinical Therapeutics
- Partner nations
- JapanUnited States
In The Last Decade
M Maruyama
21 papers receiving 446 citations
Peers
Comparison fields: 5 of 72
- Molecular Biology 144
- Epidemiology 117
- Immunology 110
- Rheumatology 101
- Genetics 88
Countries citing papers authored by M Maruyama
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
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-authorship network of co-authors of M Maruyama
This figure shows the co-authorship network connecting the top 25 collaborators of M Maruyama. A scholar is included among the top collaborators of M 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 M Maruyama. M Maruyama is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 22 | |
| 2 | 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- | 6 |
| 3 | 92 | |
| 4 | 29 | |
| 5 | 11 | |
| 6 | 11 | |
| 7 | 13 | |
| 8 | Altered levels of adipocytokines in association with insulin resistance in patients with systemic lupus erythematosus. | 116 |
| 9 | 4 | |
| 10 | 2 | |
| 11 | 6 | |
| 12 | 5 | |
| 13 | 1 | |
| 14 | 4 | |
| 15 | 4 | |
| 16 | [Epidemiology of IDDM]. | 2 |
| 17 | Cell-cycle kinetics and VSV-G pseudotyped retrovirus-mediated gene transfer in blood-derived CD34+ cells. | 37 |
| 18 | Mobilization and purification of CD34+ cells from normal donors-regimens with G-CSF, GM-CSF, or a combination of both. | 7 |
| 19 | 84 | |
| 20 | 8 |
About M Maruyama
M Maruyama is a scholar working on Nephrology, Hepatology and Transplantation, having authored 21 papers that have together received 465 indexed citations. Recurring topics across this work include Virus-based gene therapy research (5 papers), Liver physiology and pathology (5 papers) and RNA Interference and Gene Delivery (4 papers). The work is most often cited by research in Virology (51 citations), Nephrology (72 citations) and Rheumatology (101 citations). M Maruyama has collaborated with scholars based in Japan and United States. Frequent co-authors include Yohei Maeshima, Ken‐ei Sada, Hirofumi Makino, Hitoshi Sugiyama, Kazuhiro Yamauchi, Toshiki Fukui, Tadashi Yasuda, Youichi Abe, D.J. Young and Yasushi Yamasaki. Their work appears in journals such as Proceedings of the National Academy of Sciences, Diabetes Research and Clinical Practice and Clinical Therapeutics.
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.