Hidefumi Mitsuno

1.5k total citations
43 papers, 1.1k citations indexed

About

Hidefumi Mitsuno is a scholar working on Cellular and Molecular Neuroscience, Insect Science and Sensory Systems. According to data from OpenAlex, Hidefumi Mitsuno has authored 43 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Cellular and Molecular Neuroscience, 29 papers in Insect Science and 24 papers in Sensory Systems. Recurrent topics in Hidefumi Mitsuno's work include Neurobiology and Insect Physiology Research (27 papers), Olfactory and Sensory Function Studies (24 papers) and Insect Pheromone Research and Control (23 papers). Hidefumi Mitsuno is often cited by papers focused on Neurobiology and Insect Physiology Research (27 papers), Olfactory and Sensory Function Studies (24 papers) and Insect Pheromone Research and Control (23 papers). Hidefumi Mitsuno collaborates with scholars based in Japan, United States and Malaysia. Hidefumi Mitsuno's co-authors include Ryohei Kanzaki, Takeshi Sakurai, Takaaki Nishi­oka, Takao Nakagawa, Yasuhisa Endo, Yuji Yasukochi, Hajime Mori, Kazushige Touhara, Nobuo Misawa and Shoji Takeuchi and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Analytical Chemistry and Scientific Reports.

In The Last Decade

Hidefumi Mitsuno

39 papers receiving 1.1k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Hidefumi Mitsuno Japan 14 827 683 461 313 271 43 1.1k
Colm Carraher New Zealand 18 636 0.8× 522 0.8× 379 0.8× 203 0.6× 155 0.6× 30 1.0k
Yali V. Zhang United States 8 541 0.7× 248 0.4× 190 0.4× 238 0.8× 92 0.3× 11 827
K. Raming Germany 22 1.8k 2.2× 1.1k 1.7× 743 1.6× 773 2.5× 150 0.6× 32 2.2k
Tatsuro Nakagawa Japan 7 1.2k 1.4× 834 1.2× 659 1.4× 222 0.7× 30 0.1× 10 1.3k
T.A. Christensen United States 13 1.2k 1.4× 691 1.0× 483 1.0× 541 1.7× 50 0.2× 16 1.4k
Marien de Bruyne Australia 18 1.5k 1.9× 1.0k 1.5× 834 1.8× 523 1.7× 58 0.2× 23 1.9k
Abu Farhan Germany 8 646 0.8× 418 0.6× 369 0.8× 109 0.3× 23 0.1× 10 884
Ana F. Silbering Switzerland 16 1.5k 1.8× 624 0.9× 781 1.7× 331 1.1× 36 0.1× 18 1.7k
Tatsuaki Shibuya Japan 18 601 0.7× 298 0.4× 172 0.4× 445 1.4× 201 0.7× 38 867
Sabine Balfanz Germany 18 762 0.9× 547 0.8× 359 0.8× 43 0.1× 24 0.1× 30 1.1k

Countries citing papers authored by Hidefumi Mitsuno

Since Specialization
Citations

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

Fields of papers citing papers by Hidefumi Mitsuno

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hidefumi Mitsuno

This figure shows the co-authorship network connecting the top 25 collaborators of Hidefumi Mitsuno. A scholar is included among the top collaborators of Hidefumi Mitsuno based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Hidefumi Mitsuno. Hidefumi Mitsuno is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
2.
Mitsuno, Hidefumi, et al.. (2023). Gas-phase odor mixture quantification based on relative comparison method using multiple olfactory receptors. Sensors and Actuators B Chemical. 401. 134995–134995. 3 indexed citations
3.
Mitsuno, Hidefumi, et al.. (2023). Gas-Phase Odorant Fast Quantification by Odor Biosensor Based on Reference Response Model. IEEE Sensors Journal. 23(20). 24169–24178. 3 indexed citations
4.
5.
Mitsuno, Hidefumi, et al.. (2022). Study of Liquid Film Thickness for Gas Phase Odor Biosensor. IEEE Sensors Journal. 22(17). 16785–16793. 7 indexed citations
6.
Mitsuno, Hidefumi, et al.. (2021). Gas Phase Odorant Detection by Insect Olfactory Receptor. IEEE Sensors Journal. 21(19). 21184–21191. 11 indexed citations
7.
Mitsuno, Hidefumi, et al.. (2021). Extending lifetime of gas-phase odor biosensor using liquid thickness control and liquid exchange. Biosensors and Bioelectronics. 199. 113887–113887. 11 indexed citations
8.
Mitsuno, Hidefumi, et al.. (2021). Binary mixture quantification using cell-based odor biosensor system with active sensing. Biosensors and Bioelectronics. 179. 113053–113053. 15 indexed citations
9.
Fujii, Takeshi, Takeshi Sakurai, Hidefumi Mitsuno, et al.. (2020). Pheromonal activities of the bombykol isomer, (10E,12E)-10,12-hexadecadien-1-ol, in the pheromone gland of the silkmoth Bombyx mori. Journal of Insect Physiology. 121. 104018–104018. 2 indexed citations
10.
Mitsuno, Hidefumi, et al.. (2019). Odor Discrimination Using Cell-Based Odor Biosensor System With Fluorescent Image Processing. IEEE Sensors Journal. 19(17). 7192–7200. 15 indexed citations
11.
Fujii, Takeshi, et al.. (2019). 昆虫のフェロモン2. KAGAKU TO SEIBUTSU. 57(12). 749–759.
12.
Ono, Hajime, et al.. (2019). Functional characterization of olfactory receptors in three Dacini fruit flies (Diptera: Tephritidae) that respond to 1-nonanol analogs as components in the rectal glands. Comparative Biochemistry and Physiology Part B Biochemistry and Molecular Biology. 239. 110346–110346. 11 indexed citations
13.
Mitsuno, Hidefumi, Katsuhisa Ozaki, Ryohei Kanzaki, et al.. (2018). Functional characterization of olfactory receptors in the Oriental fruit fly Bactrocera dorsalis that respond to plant volatiles. Insect Biochemistry and Molecular Biology. 101. 32–46. 45 indexed citations
14.
Sakurai, Takeshi, Takaaki Daimon, Hidefumi Mitsuno, et al.. (2018). In vivo functional characterisation of pheromone binding protein-1 in the silkmoth, Bombyx mori. Scientific Reports. 8(1). 13529–13529. 35 indexed citations
15.
Nakamoto, Takamichi, et al.. (2017). Sensitivity Improvement by Applying Lock-In Technique to Fluorescent Instrumentation for Cell-Based Odor Sensor. Sensors and Materials. 65–65. 11 indexed citations
16.
Nakamoto, Takamichi, et al.. (2016). Development of Automated Flow Measurement System for Cell-based Odor Sensor. IEEJ Transactions on Sensors and Micromachines. 136(7). 289–295. 2 indexed citations
17.
Miyamoto, Daisuke, Hidefumi Mitsuno, Takeshi Fujii, et al.. (2016). Identification of repellent odorants to the body louse, Pediculus humanus corporis, in clove essential oil. Parasitology Research. 115(4). 1659–1666. 5 indexed citations
18.
Mitsuno, Hidefumi, Nobuo Misawa, Shinya Yamahira, et al.. (2016). Cell-Based Odorant Sensor Array for Odor Discrimination Based on Insect Odorant Receptors. Journal of Chemical Ecology. 42(7). 716–724. 45 indexed citations
19.
Sakurai, Takeshi, Hidefumi Mitsuno, Keiro Uchino, et al.. (2015). Targeted disruption of a single sex pheromone receptor gene completely abolishes in vivo pheromone response in the silkmoth. Scientific Reports. 5(1). 11001–11001. 32 indexed citations
20.
Sakurai, Takeshi, et al.. (2012). Dissociated neuronal culture expressing ionotropic odorant receptors as a hybrid odorant biosensor—proof-of-concept study. The Analyst. 137(15). 3452–3452. 7 indexed citations

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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