Takeshi Ōmasa
- Biotechnology top 2%
- Transgenic Plants and Applications 13
- Molecular Biology top 5%
- Viral Infectious Diseases and Gene Expression in Insects 76
- Protein purification and stability 42
- Microbial Metabolic Engineering and Bioproduction 19
- CRISPR and Genetic Engineering 18
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- Monoclonal and Polyclonal Antibodies Research 48
- Hepatology top 5%
- Liver physiology and pathology 13
- Genetics top 5%
- Virus-based gene therapy research 17
- Co-authors
- Hisao OhtakeKohsuke HondaKen‐ichi SugaMasayoshi OnitsukaMichimasa KishimotoYoshio KatakuraSuteaki ShioyaWook-Dong Kim
- Journals
- Applied and Environmental Microbiology (1 paper)Scientific Reports (3 papers)Biochemical and Biophysical Research Communications (1 paper)
- Partner nations
- JapanUnited StatesChina
In The Last Decade
Takeshi Ōmasa
161 papers receiving 2.7k citations
Peers
Comparison fields: 5 of 135
- Biotechnology 299
- Molecular Biology 2.1k
- Radiology, Nuclear Medicine and Imaging 549
- Hepatology 145
- Genetics 504
Countries citing papers authored by Takeshi Ōmasa
This map shows the geographic impact of Takeshi Ōmasa'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 Takeshi Ōmasa with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Takeshi Ōmasa more than expected).
Fields of papers citing papers by Takeshi Ōmasa
This network shows the impact of papers produced by Takeshi Ōmasa. 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 Takeshi Ōmasa. The network helps show where Takeshi Ōmasa may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Takeshi Ōmasa, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 0 | |
| 2 | 2024 | 3 | |
| 3 | 2024 | 2 | |
| 4 | 2024 | 1 | |
| 5 | 2023 | 19 | |
| 6 | 2019 | 39 | |
| 7 | 2019 | 4 | |
| 8 | Analysis of intracellular recombinant IgG secretion in engineered CHO cells | 2016 | 0 |
| 9 | 2016 | 6 | |
| 10 | 2013 | 28 | |
| 11 | 2013 | 17 | |
| 12 | 2013 | 12 | |
| 13 | 2013 | 13 | |
| 14 | 2011 | 9 | |
| 15 | 2011 | 34 | |
| 16 | 2008 | 8 | |
| 17 | 2008 | 48 | |
| 18 | 2002 | 2 | |
| 19 | 2001 | 4 | |
| 20 | 1995 | 4 |
About Takeshi Ōmasa
Takeshi Ōmasa is a scholar working on Radiology, Nuclear Medicine and Imaging, Molecular Biology and Biotechnology, having authored 168 papers that have together received 2.8k indexed citations. Recurring topics across this work include Viral Infectious Diseases and Gene Expression in Insects (76 papers), Monoclonal and Polyclonal Antibodies Research (48 papers), Protein purification and stability (42 papers), Microbial Metabolic Engineering and Bioproduction (19 papers), CRISPR and Genetic Engineering (18 papers), Virus-based gene therapy research (17 papers), Liver physiology and pathology (13 papers) and Transgenic Plants and Applications (13 papers). The work is most often cited by research in Biotechnology (299 citations), Molecular Biology (2.1k citations) and Radiology, Nuclear Medicine and Imaging (549 citations). Takeshi Ōmasa has collaborated with scholars based in Japan, United States and China. Frequent co-authors include Hisao Ohtake, Kohsuke Honda, Ken‐ichi Suga, Masayoshi Onitsuka, Michimasa Kishimoto, Yoshio Katakura, Suteaki Shioya, Wook-Dong Kim, Kenichi Higashiyama and Akihiro Shirai. Their work appears in journals such as Applied and Environmental Microbiology, Scientific Reports and Biochemical and Biophysical Research Communications.
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.