Jiro Arima

1.3k citations
72 papers · 1.1k indexed · h-index 18

Jiro Arima

69 papers receiving 991 citations

Peers

Jiro Arima
Comparison fields: 5 of 91
  • Biotechnology 219
  • Biochemistry 105
  • Oncology 287
  • Molecular Biology 703
  • Cellular and Molecular Neuroscience 135
Replace Ken-Ichi Kusumoto with:
Ken-Ichi Kusumoto Japan
Takashi Shin Japan
Jung Min Park South Korea
Konrad Urech Germany
Eiko Tsuchiya Japan
Hai‐Meng Zhou China
Per Greisen United States
Qin Shu China
Dominic P. H. M. Heuts Netherlands
Tiziana Lodi Italy
Jiro Arima relative to Ken-Ichi Kusumoto Japan Ken-Ichi Kusumoto's profile →
Citations per field
00.5×
Ken-Ichi Kusumoto · 1×
Citations per year

Countries citing papers authored by Jiro Arima

Since Specialization
Citations

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

Fields of papers citing papers by Jiro Arima

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20183
2 20171
3 20158
4 201428
5
Evaluation of genes encoding 4-N-trimethylaminobutyraldehyde dehydrogenase and 4-N-trimethylamino-1-butanol dehydrogenase from Pseudomonas sp. 13CM.
20131
6 20130
7 20128
8 2012223
9 20121
10 20119
11 20119
12 20117
13 20119
14 20099
15 20096
16 200620
17 20066
18 200536
19 200525
20 19886

About Jiro Arima

Jiro Arima is a scholar working on Biochemistry, Biotechnology, Oncology, Molecular Biology and Aging, having authored 72 papers that have together received 1.1k indexed citations. Recurring topics across this work include Peptidase Inhibition and Analysis (26 papers), Amino Acid Enzymes and Metabolism (14 papers), Chemical Synthesis and Analysis (12 papers), Enzyme Production and Characterization (9 papers), Neuropeptides and Animal Physiology (8 papers), Enzyme Structure and Function (7 papers), Biofuel production and bioconversion (7 papers) and Polyamine Metabolism and Applications (7 papers). The work is most often cited by research in Biotechnology (219 citations), Biochemistry (105 citations), Oncology (287 citations), Molecular Biology (703 citations) and Cellular and Molecular Neuroscience (135 citations). Jiro Arima has collaborated with scholars based in Japan, Canada and Sudan. Frequent co-authors include Tadashi Hatanaka, Masaki Iwabuchi, Yoshiko Uesugi, Hirokazu Usuki, Yuya Kumagai, Takafumi Mukaihara, Misugi Uraji, Nobuhiro Mori, Kayoko Kawakami and Katsuhiko Shimizu. Their work appears in journals such as Applied and Environmental Microbiology, Bioscience Biotechnology and Biochemistry, Biochimica et Biophysica Acta (BBA) - Proteins and Proteomics, Applied Microbiology and Biotechnology and World Journal of Microbiology and Biotechnology.

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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