M Maeda

4.0k citations
117 papers · 3.3k · h-index 31

Impact in

Papers in

M Maeda

115 papers receiving 3.1k citations

Peers

M Maeda
Comparison fields: 5 of 119
  • Applied Microbiology and Biotechnology 185
  • Immunology 1.5k
  • Agronomy and Crop Science 589
  • Immunology and Allergy 146
  • Ecology, Evolution, Behavior and Systematics 461
Replace Enzo Bonmassar with:
Enzo Bonmassar Italy
Ulrike Kämmerer Germany
Dirck L. Dillehay United States
Lei Li China
Hirokuni Taguchi Japan
Teruhiko Tamaya Japan
Feng Ma China
David R. Scott United States
Jean‐François Peyron France
B B Aggarwal United States
M Maeda relative to Enzo Bonmassar Italy Enzo Bonmassar's profile →
Citations per field
00.5×5×10×14.2×
Enzo Bonmassar · 1×
Citations per year

Countries citing papers authored by M Maeda

Since Specialization
Citations

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

Fields of papers citing papers by M Maeda

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside M Maeda, 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 Maeda Line = papers co-authored together M Maeda links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 117 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1996271
2 1990250
3 1985215
4 1985160
5 1998114
6
Adult T leukemia cells produce a lymphokine that augments interleukin 2 receptor expression.
1985101
7 1983100
8 198774
9 200172
10 199871
11
Production of hydrogen peroxide and methionine sulfoxide by epigallocatechin gallate and antioxidants.
200167
12 198961
13 201860
14 200058
15 198357
16 200555
17 199748
18 199448
19 197648
20 200343

About M Maeda

M Maeda is a scholar working on Immunology, Molecular Biology, Applied Microbiology and Biotechnology, Agronomy and Crop Science and Ecology, Evolution, Behavior and Systematics, having authored 117 papers that have together received 3.3k indexed citations. Recurring topics across this work include T-cell and Retrovirus Studies (18 papers), Antibiotic Use and Resistance (18 papers), Vector-Borne Animal Diseases (13 papers), Animal Disease Management and Epidemiology (12 papers), Reproductive System and Pregnancy (10 papers), Antibiotic Resistance in Bacteria (8 papers), Cell Adhesion Molecules Research (6 papers) and Patient Satisfaction in Healthcare (6 papers). The work is most often cited by research in Applied Microbiology and Biotechnology (185 citations), Immunology (1.5k citations), Agronomy and Crop Science (589 citations), Immunology and Allergy (146 citations) and Ecology, Evolution, Behavior and Systematics (461 citations). M Maeda has collaborated with scholars based in Japan, United States and Croatia. Frequent co-authors include Takashi Uchiyama, Junji Yodoi, Hiroshi Fujiwara, Akio Tsuji, A Yoshida, Naomi Wakasugi, Akira Mitsui, Hiro Wakasugi, Thomas Tursz and Y Tagaya. Their work appears in journals such as The Journal of Clinical Endocrinology & Metabolism, Human Reproduction, Blood, The Journal of Experimental Medicine and Antibiotics.

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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