Akira Muto

5.3k total citations
97 papers, 4.0k citations indexed

About

Akira Muto is a scholar working on Molecular Biology, Cell Biology and Ecology. According to data from OpenAlex, Akira Muto has authored 97 papers receiving a total of 4.0k indexed citations (citations by other indexed papers that have themselves been cited), including 49 papers in Molecular Biology, 24 papers in Cell Biology and 18 papers in Ecology. Recurrent topics in Akira Muto's work include Zebrafish Biomedical Research Applications (19 papers), Bacteriophages and microbial interactions (17 papers) and RNA and protein synthesis mechanisms (15 papers). Akira Muto is often cited by papers focused on Zebrafish Biomedical Research Applications (19 papers), Bacteriophages and microbial interactions (17 papers) and RNA and protein synthesis mechanisms (15 papers). Akira Muto collaborates with scholars based in Japan, United States and Germany. Akira Muto's co-authors include S. Osawa, Koichi Kawakami, Herwig Baier, Syozo Osawa, Fumiaki Yamao, Shoen Kume, Hideyuki Okano, Junichi Nakai, Masamichi Ohkura and Masafumi Iwami and has published in prestigious journals such as Nature, Science and Cell.

In The Last Decade

Akira Muto

94 papers receiving 4.0k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Akira Muto Japan 34 2.4k 1.1k 670 619 490 97 4.0k
Guy P. Richardson United Kingdom 57 3.8k 1.6× 855 0.7× 632 0.9× 621 1.0× 359 0.7× 146 9.2k
Peter G. Gillespie United States 49 4.1k 1.7× 1.0k 0.9× 784 1.2× 430 0.7× 273 0.6× 112 7.8k
Andrew Forge United Kingdom 46 3.5k 1.4× 564 0.5× 432 0.6× 559 0.9× 382 0.8× 131 8.2k
Jeffrey J. Wine United States 47 2.3k 0.9× 416 0.4× 1.6k 2.4× 802 1.3× 662 1.4× 139 7.5k
Clifton W. Ragsdale United States 32 3.9k 1.6× 358 0.3× 2.5k 3.7× 591 1.0× 1.1k 2.3× 53 7.2k
Jan van Minnen Netherlands 41 2.5k 1.0× 480 0.4× 2.7k 4.1× 421 0.7× 248 0.5× 124 5.5k
Richard Hawkes Canada 57 6.1k 2.5× 1.5k 1.3× 4.2k 6.3× 299 0.5× 906 1.8× 162 12.2k
Corné J. Kros United Kingdom 43 2.3k 0.9× 303 0.3× 744 1.1× 364 0.6× 104 0.2× 73 6.1k
Toshiro Aigaki Japan 39 2.6k 1.1× 775 0.7× 1.9k 2.9× 202 0.3× 1.4k 2.8× 138 5.5k
Stefan Dübel Germany 56 7.4k 3.1× 473 0.4× 2.3k 3.4× 938 1.5× 454 0.9× 220 9.7k

Countries citing papers authored by Akira Muto

Since Specialization
Citations

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

Fields of papers citing papers by Akira Muto

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Akira Muto

This figure shows the co-authorship network connecting the top 25 collaborators of Akira Muto. A scholar is included among the top collaborators of Akira Muto 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 Akira Muto. Akira Muto 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.
Muto, Akira, et al.. (2019). Six6 and Six7 coordinately regulate expression of middle-wavelength opsins in zebrafish. Proceedings of the National Academy of Sciences. 116(10). 4651–4660. 31 indexed citations
2.
Lal, Pradeep, Hideyuki Tanabe, Maximiliano L. Suster, et al.. (2018). Identification of a neuronal population in the telencephalon essential for fear conditioning in zebrafish. BMC Biology. 16(1). 45–45. 82 indexed citations
3.
Muto, Akira, Pradeep Lal, Deepak Ailani, et al.. (2017). Activation of the hypothalamic feeding centre upon visual prey detection. Nature Communications. 8(1). 15029–15029. 78 indexed citations
4.
Kawakami, Koichi, Kazuhide Asakawa, Masahiko Hibi, et al.. (2016). Gal4 Driver Transgenic Zebrafish. Advances in genetics. 95. 65–87. 47 indexed citations
5.
Kawakami, Koichi, Kazuhide Asakawa, Akira Muto, & Hironori Wada. (2016). Tol2-mediated transgenesis, gene trapping, enhancer trapping, and Gal4-UAS system. Methods in cell biology. 19–37. 18 indexed citations
6.
Muto, Akira & Koichi Kawakami. (2016). Calcium Imaging of Neuronal Activity in Free-Swimming Larval Zebrafish. Methods in molecular biology. 1451. 333–341. 12 indexed citations
7.
Ogino, Kazutoyo, Sean E. Low, Kenta Yamada, et al.. (2015). RING finger protein 121 facilitates the degradation and membrane localization of voltage-gated sodium channels. Proceedings of the National Academy of Sciences. 112(9). 2859–2864. 19 indexed citations
8.
Muto, Akira, Masamichi Ohkura, Gembu Abe, Junichi Nakai, & Koichi Kawakami. (2013). Real-Time Visualization of Neuronal Activity during Perception. Current Biology. 23(4). 307–311. 178 indexed citations
9.
Hirata, Hiromi, Hua Wen, Yu Kawakami, et al.. (2011). Connexin 39.9 Protein Is Necessary for Coordinated Activation of Slow-twitch Muscle and Normal Behavior in Zebrafish. Journal of Biological Chemistry. 287(2). 1080–1089. 12 indexed citations
10.
Harada, Mamoru, Satoko Matsueda, Akira Muto, et al.. (2004). In Vivo Evidence That Peptide Vaccination Can Induce HLA-DR-Restricted CD4+ T Cells Reactive to a Class I Tumor Peptide. The Journal of Immunology. 172(4). 2659–2667. 15 indexed citations
11.
Orger, Michael B., Ethan Gahtan, Akira Muto, et al.. (2004). Behavioral Screening Assays in Zebrafish. Methods in cell biology. 77. 53–68. 74 indexed citations
12.
Muto, Akira, et al.. (1998). Effect of Grain Size on Dead Load Creep Test of OFHC-Cu and 7-3 Brass at Elevated Temperatures.. 11(1). 52–60. 3 indexed citations
13.
Muto, Akira & Katsuhiko Mikoshiba. (1998). Activation of inositol 1,4,5-trisphosphate receptors induces transient changes in cell shape of fertilizedXenopus eggs. Cell Motility and the Cytoskeleton. 39(3). 201–208. 11 indexed citations
14.
Sato, Tadao, et al.. (1997). Magnetic Impulse Welding of Aluminum Tube and Copper Tube with Some Kinds of Metal Tubes. Study on Magnetic Impulse Welding (Report 1).. QUARTERLY JOURNAL OF THE JAPAN WELDING SOCIETY. 15(4). 615–622. 2 indexed citations
15.
16.
Kume, Shoen, Akira Muto, Hideyuki Okano, & Katsuhiko Mikoshiba. (1997). Developmental expression of the inositol 1,4,5-trisphosphate receptor and localization of inositol 1,4,5-trisphosphate during early embryogenesis in Xenopus laevis. Mechanisms of Development. 66(1-2). 157–168. 29 indexed citations
17.
Himeno, Hyouta, Masakazu Sato, Toshimasa Tadaki, et al.. (1997). In vitro Trans Translation mediated by alanine-charged 10sa RNA. Journal of Molecular Biology. 268(5). 803–808. 80 indexed citations
18.
Kume, Shoen, Akira Muto, Jun Aruga, et al.. (1993). The Xenopus IP3 receptor: Structure, function, and localization in oocytes and eggs. Cell. 73(3). 555–570. 197 indexed citations
19.
Andachi, Yoshiki, et al.. (1991). Translation in vitro of codon UGA as tryptophan in Mycoplasma capricolum. Biochimie. 73(7-8). 1109–1112. 11 indexed citations
20.
Whitley, Jane C., et al.. (1991). A physical map forMycoplasma capricolumCal. kid with loci for all known tRNA species. Nucleic Acids Research. 19(2). 399–400. 23 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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