Iori Maeda
Impact in
- Biomaterials top 10%
- Supramolecular Self-Assembly in Materials
- Silk-based biomaterials and applications
- Genetics top 10%
- Connective tissue disorders research
Papers in
- Genetics 24
- Connective tissue disorders research 24
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- Chemical Synthesis and Analysis 6
- Protein Hydrolysis and Bioactive Peptides 5
- Co-authors
- Takeru Nose (24 shared papers)Yasuyuki Shimohigashi (8 shared papers)Kouji Okamoto (7 shared papers)Keitaro Suyama (13 shared papers)Noriko Watanabe (3 shared papers)Motonori Ohno (4 shared papers)Koji Okamoto (3 shared papers)Yuji Yamamoto (1 shared paper)
- Journals
- Journal of Peptide Science (8 papers)The Journal of Biochemistry (4 papers)Biomacromolecules (2 papers)Biopolymers (2 papers)Biochemistry (2 papers)
- Partner nations
- JapanUnited StatesBelarus
In The Last Decade
Iori Maeda
38 papers receiving 488 citations
Peers
Comparison fields: 5 of 72
- Biomaterials 116
- Genetics 213
- Cancer Research 75
- Physical and Theoretical Chemistry 36
- Rheumatology 42
Countries citing papers authored by Iori Maeda
This map shows the geographic impact of Iori 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 Iori Maeda with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Iori Maeda more than expected).
Fields of papers citing papers by Iori Maeda
This network shows the impact of papers produced by Iori 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 Iori Maeda. The network helps show where Iori Maeda may publish in the future.
Co-authors
The 25 scholars most cited alongside Iori 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 39 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2002 | 38 | |
| 2 | 2008 | 29 | |
| 3 | 1999 | 29 | |
| 4 | 2017 | 29 | |
| 5 | 1998 | 28 | |
| 6 | 1996 | 28 | |
| 7 | 2007 | 27 | |
| 8 | 2011 | 25 | |
| 9 | 2007 | 24 | |
| 10 | 2010 | 21 | |
| 11 | 2015 | 20 | |
| 12 | 2015 | 16 | |
| 13 | 2018 | 15 | |
| 14 | 2013 | 14 | |
| 15 | 1996 | 12 | |
| 16 | 2022 | 12 | |
| 17 | 2021 | 12 | |
| 18 | 2016 | 12 | |
| 19 | 2016 | 11 | |
| 20 | 1993 | 11 |
About Iori Maeda
Iori Maeda is a scholar working on Genetics, Molecular Biology, Biomaterials, Cancer Research and Oncology, having authored 39 papers that have together received 496 indexed citations. Recurring topics across this work include Connective tissue disorders research (24 papers), Protease and Inhibitor Mechanisms (9 papers), Supramolecular Self-Assembly in Materials (8 papers), Chemical Synthesis and Analysis (6 papers), Protein Hydrolysis and Bioactive Peptides (5 papers), Peptidase Inhibition and Analysis (5 papers), Bone and Dental Protein Studies (4 papers) and Cell Adhesion Molecules Research (3 papers). The work is most often cited by research in Biomaterials (116 citations), Genetics (213 citations), Cancer Research (75 citations), Physical and Theoretical Chemistry (36 citations) and Rheumatology (42 citations). Iori Maeda has collaborated with scholars based in Japan, United States and Belarus. Frequent co-authors include Takeru Nose, Yasuyuki Shimohigashi, Kouji Okamoto, Keitaro Suyama, Noriko Watanabe, Motonori Ohno, Koji Okamoto, Yuji Yamamoto, Masaya Sakamoto and Jing Meng. Their work appears in journals such as Journal of Peptide Science, The Journal of Biochemistry, Biomacromolecules, Biopolymers and Biochemistry.
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.