Daisuke Tsuru

136 papers receiving 2.7k citations

Peers

Daisuke Tsuru
Comparison fields: 5 of 118
  • Biotechnology 552
  • Oncology 1.3k
  • Cellular and Molecular Neuroscience 681
  • Molecular Biology 1.7k
  • Biochemistry 119
Replace Tadashi Yoshimoto with:
Tadashi Yoshimoto Japan
Jules A. Gladner United States
Nathan N. Aronson United States
Long Ma China
Peter K. Chiang United States
Akira Matsuura Japan
Takashi Sasaki Japan
Hideo Chiba Japan
Yigal Burstein Israel
H. R. Maurer Germany
Daisuke Tsuru relative to Tadashi Yoshimoto Japan Tadashi Yoshimoto's profile →
Citations per field
00.5×1.5×
Tadashi Yoshimoto · 1×
Citations per year

Countries citing papers authored by Daisuke Tsuru

Since Specialization
Citations

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

Fields of papers citing papers by Daisuke Tsuru

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 139 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1996215
2 1987154
3 1979152
4 1964129
5 1991126
6 198372
7 199166
8
Formaldehyde dehydrogenase from Pseudomonas putida. Purification and some properties.
197963
9 198162
10 199157
11 198857
12 197149
13 197846
14 199044
15 200241
16
New chromogenic and fluorogenic substrates for pyrrolidonyl peptidase.
197841
17 198939
18 199438
19 198336
20 197836

About Daisuke Tsuru

Daisuke Tsuru is a scholar working on Molecular Biology, Biotechnology, Oncology, Cellular and Molecular Neuroscience and Materials Chemistry, having authored 139 papers that have together received 2.8k indexed citations. Recurring topics across this work include Enzyme Production and Characterization (57 papers), Peptidase Inhibition and Analysis (53 papers), Neuropeptides and Animal Physiology (28 papers), Protein Hydrolysis and Bioactive Peptides (25 papers), Enzyme Structure and Function (20 papers), Phytase and its Applications (12 papers), Biochemical and Structural Characterization (11 papers) and Advanced Combustion Engine Technologies (11 papers). The work is most often cited by research in Biotechnology (552 citations), Oncology (1.3k citations), Cellular and Molecular Neuroscience (681 citations), Molecular Biology (1.7k citations) and Biochemistry (119 citations). Daisuke Tsuru has collaborated with scholars based in Japan, United States and Switzerland. Frequent co-authors include Tadashi Yoshimoto, Kunio Fujiwara, Juichiro FUKUMOTO, Kerry T. Yasunobu, James McConn, Takehiko Yamamoto, Futoshi Matsubara, Taizo Kita, Takamasa Nonaka and Yukio Mitsui. Their work appears in journals such as The Journal of Biochemistry, Bioscience Biotechnology and Biochemistry, SAE technical papers on CD-ROM/SAE technical paper series, Archives of Biochemistry and Biophysics and Journal of Histochemistry & Cytochemistry.

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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