Sumio Maeda
Impact in
- Molecular Medicine top 5%
- Antibiotic Resistance in Bacteria
- Endocrinology top 10%
Papers in
- Genetics 19
- Bacterial Genetics and Biotechnology 17
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- Liver physiology and pathology 9
- Co-authors
- Takao Saito (12 shared papers)Érika Suzuki (3 shared papers)Hidetoshi Inagaki (12 shared papers)Katsuya Kato (3 shared papers)Akiko Matsuda (2 shared papers)Miki Ito (4 shared papers)Takeshi Mizuno (2 shared papers)Takao Saito (7 shared papers)
- Journals
- Biochemical and Biophysical Research Communications (6 papers)World Journal of Microbiology and Biotechnology (3 papers)Medical Mycology (3 papers)Bioscience Biotechnology and Biochemistry (3 papers)Frontiers in Microbiology (2 papers)
- Partner nations
- JapanUnited StatesCanada
In The Last Decade
Sumio Maeda
50 papers receiving 853 citations
Peers
Comparison fields: 5 of 99
- Molecular Medicine 112
- Endocrinology 66
- Biotechnology 96
- Pollution 104
- Genetics 231
Countries citing papers authored by Sumio Maeda
This map shows the geographic impact of Sumio 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 Sumio Maeda with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sumio Maeda more than expected).
Fields of papers citing papers by Sumio Maeda
This network shows the impact of papers produced by Sumio 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 Sumio Maeda. The network helps show where Sumio Maeda may publish in the future.
Co-authors
The 25 scholars most cited alongside Sumio Maeda, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 50 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2003 | 76 | |
| 2 | 2018 | 74 | |
| 3 | 2005 | 70 | |
| 4 | 2018 | 62 | |
| 5 | 1988 | 44 | |
| 6 | hst-1 transforming protein: expression in silkworm cells and characterization as a novel heparin-binding growth factor. | 1988 | 38 |
| 7 | 1992 | 38 | |
| 8 | 2011 | 35 | |
| 9 | 2004 | 33 | |
| 10 | 1995 | 32 | |
| 11 | 2019 | 28 | |
| 12 | 1998 | 26 | |
| 13 | 1991 | 25 | |
| 14 | 2000 | 24 | |
| 15 | 2009 | 20 | |
| 16 | 1993 | 20 | |
| 17 | 1998 | 18 | |
| 18 | 2003 | 15 | |
| 19 | 1994 | 15 | |
| 20 | 1996 | 14 |
About Sumio Maeda
Sumio Maeda is a scholar working on Genetics, Hepatology, Molecular Biology, Ecology and Biotechnology, having authored 50 papers that have together received 885 indexed citations. Recurring topics across this work include Bacterial Genetics and Biotechnology (17 papers), Bacteriophages and microbial interactions (14 papers), Liver physiology and pathology (9 papers), Bacterial biofilms and quorum sensing (8 papers), CRISPR and Genetic Engineering (8 papers), RNA and protein synthesis mechanisms (5 papers), Fungal Infections and Studies (3 papers) and Enzyme Production and Characterization (3 papers). The work is most often cited by research in Molecular Medicine (112 citations), Endocrinology (66 citations), Biotechnology (96 citations), Pollution (104 citations) and Genetics (231 citations). Sumio Maeda has collaborated with scholars based in Japan, United States and Canada. Frequent co-authors include Takao Saito, Érika Suzuki, Hidetoshi Inagaki, Katsuya Kato, Akiko Matsuda, Miki Ito, Takeshi Mizuno, Takao Saito, Kai‐Hsin Lin and Yoshiyuki Yokogawa. Their work appears in journals such as Biochemical and Biophysical Research Communications, World Journal of Microbiology and Biotechnology, Medical Mycology, Bioscience Biotechnology and Biochemistry and Frontiers in Microbiology.
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.