Yuko Kusakabe

2.5k total citations
55 papers, 2.0k citations indexed

About

Yuko Kusakabe is a scholar working on Nutrition and Dietetics, Sensory Systems and Biomedical Engineering. According to data from OpenAlex, Yuko Kusakabe has authored 55 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 46 papers in Nutrition and Dietetics, 41 papers in Sensory Systems and 25 papers in Biomedical Engineering. Recurrent topics in Yuko Kusakabe's work include Biochemical Analysis and Sensing Techniques (45 papers), Olfactory and Sensory Function Studies (40 papers) and Advanced Chemical Sensor Technologies (25 papers). Yuko Kusakabe is often cited by papers focused on Biochemical Analysis and Sensing Techniques (45 papers), Olfactory and Sensory Function Studies (40 papers) and Advanced Chemical Sensor Technologies (25 papers). Yuko Kusakabe collaborates with scholars based in Japan, Slovakia and United States. Yuko Kusakabe's co-authors include Hirohito Miura, Akihiro Hino, Yuzo Ninomiya, Michinori Kitagawa, Yasufumi Emori, Keiko Abe, Shuitsu Harada, Noriatsu Shigemura, Soichi Arai and Yoichiro Shindo and has published in prestigious journals such as Journal of Biological Chemistry, Nature Communications and PLoS ONE.

In The Last Decade

Yuko Kusakabe

53 papers receiving 1.9k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Yuko Kusakabe Japan 27 1.4k 1.1k 677 665 236 55 2.0k
Minqing Rong United States 15 1.5k 1.1× 1.4k 1.2× 752 1.1× 783 1.2× 306 1.3× 21 2.3k
Vicktoria Danilova United States 19 1.1k 0.8× 1.0k 0.9× 221 0.3× 623 0.9× 228 1.0× 24 1.5k
Alison J. Vigers United States 8 445 0.3× 408 0.4× 413 0.6× 240 0.4× 144 0.6× 9 1.2k
Takashi Kurahashi Japan 23 878 0.6× 1.4k 1.3× 437 0.6× 411 0.6× 42 0.2× 43 2.0k
Miriam Khen Israel 13 617 0.4× 728 0.6× 290 0.4× 217 0.3× 16 0.1× 15 1.1k
Ian E. Lush United Kingdom 17 447 0.3× 297 0.3× 264 0.4× 139 0.2× 95 0.4× 31 874
Takatoshi Ohkuri Japan 16 306 0.2× 197 0.2× 562 0.8× 140 0.2× 110 0.5× 50 1.1k
Erwin Tareilus Germany 15 484 0.4× 558 0.5× 596 0.9× 101 0.2× 22 0.1× 19 1.5k
Taufiqul Huque United States 13 574 0.4× 589 0.5× 181 0.3× 237 0.4× 44 0.2× 23 813
Barbara R. Talamo United States 25 192 0.1× 264 0.2× 883 1.3× 92 0.1× 248 1.1× 42 1.8k

Countries citing papers authored by Yuko Kusakabe

Since Specialization
Citations

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

Fields of papers citing papers by Yuko Kusakabe

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yuko Kusakabe

This figure shows the co-authorship network connecting the top 25 collaborators of Yuko Kusakabe. A scholar is included among the top collaborators of Yuko Kusakabe 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 Yuko Kusakabe. Yuko Kusakabe 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
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Araki, Risa, et al.. (2023). Effect of texture preference on food texture perception: Exploring the role of matching food texture and preference. Appetite. 192. 107078–107078. 6 indexed citations
3.
Ogawa, Yukino, Kaoru Kohyama, & Yuko Kusakabe. (2020). Salivation Correlates with Masseter Muscle Activity and Partially Depends on the Physical Characteristics and Volume of Food Consumed at One Time. Food Science and Technology Research. 26(4). 535–543. 1 indexed citations
4.
Ogawa, Yukino, Takayuki Kawai, & Yuko Kusakabe. (2020). Evaluation of Taste Solutions with or without Aromas Based on the Relationship between Individual Resting and Stimulated Salivation. Food Science and Technology Research. 26(3). 451–457.
5.
Kasai, Satoshi, Tomohiro Masuda, Toshihiko Shoji, et al.. (2017). Estimation of Subjective Internal Browning Severity Ratings for Scanned Images of Fuji Apples. Food Science and Technology Research. 23(4). 545–549. 2 indexed citations
6.
GOTO, Masao, et al.. (2014). Distinct Human and Mouse Membrane Trafficking Systems for Sweet Taste Receptors T1r2 and T1r3. PLoS ONE. 9(7). e100425–e100425. 19 indexed citations
7.
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Shindo, Yutaka, Mee Ree Kim, Hiroyuki Miura, et al.. (2010). Lrmp/Jaw1 is Expressed in Sweet, Bitter, and Umami Receptor-Expressing Cells. Chemical Senses. 35(2). 171–177. 32 indexed citations
9.
Miura, Hirohito, et al.. (2008). Expression of the basal cell markers of taste buds in the anterior tongue and soft palate of the mouse embryo. The Journal of Comparative Neurology. 509(2). 211–224. 33 indexed citations
10.
Miura, Hirohito, et al.. (2003). Co-expression pattern of Shh with Prox1 and that of Nkx2.2 with Mash1 in mouse taste bud. Gene Expression Patterns. 3(4). 427–430. 50 indexed citations
11.
Kitagawa, Michinori, Yuko Kusakabe, Hirohito Miura, Yuzo Ninomiya, & Akihiro Hino. (2001). Molecular Genetic Identification of a Candidate Receptor Gene for Sweet Taste. Biochemical and Biophysical Research Communications. 283(1). 236–242. 256 indexed citations
12.
Matsuoka, Takeshi, Hideo Kuribara, Hiroshi Akiyama, et al.. (2001). A Multiplex PCR Method of Detecting Recombinant DNAs from Five Lines of Genetically Modified Maize.. Food Hygiene and Safety Science (Shokuhin Eiseigaku Zasshi). 42(1). 24–32. 108 indexed citations
13.
Miura, Hirohito, et al.. (2001). Shh and Ptc are associated with taste bud maintenance in the adult mouse. Mechanisms of Development. 106(1-2). 143–145. 90 indexed citations
14.
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Misaka, Takumi, Yoshiro Ishimaru, Yuko Kusakabe, et al.. (1999). A gustatory cyclic nucleotide-gated channels CNGgust, is expressed in the retina. Neuroreport. 10(4). 743–746. 6 indexed citations
16.
Kusakabe, Yuko, Kentaro Tanemura, Kimihiko Kameyama, et al.. (1998). Identification of two α-subunit species of GTP-binding proteins, Gα15 and Gαq, expressed in rat taste buds. Biochimica et Biophysica Acta (BBA) - Molecular Cell Research. 1403(3). 265–272. 37 indexed citations
17.
Misaka, Takumi, et al.. (1998). Molecular Cloning and Taste Bud‐Specific Expression of a Novel Cyclic Nucleotide‐Gated Channel. Annals of the New York Academy of Sciences. 855(1). 150–159. 10 indexed citations
18.
Misaka, Takumi, Yuko Kusakabe, Yasufumi Emori, et al.. (1997). Taste Buds Have a Cyclic Nucleotide-activated Channel, CNGgust. Journal of Biological Chemistry. 272(36). 22623–22629. 65 indexed citations
19.
Misaka, Takumi, Keiko Abe, Yuko Kusakabe, et al.. (1996). A water channel closely related to rat brain aquaporin 4 is expressed in acid‐ and pepsinogen‐secretory cells of human stomach. FEBS Letters. 381(3). 208–212. 50 indexed citations
20.
Abe, Keiko, Yuko Kusakabe, Kentaro Tanemura, Yasufumi Emori, & Soichi Arai. (1993). Multiple genes for G protein‐coupled receptors and their expression in lingual epithelia. FEBS Letters. 316(3). 253–256. 33 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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