Mitsuoki Kawano

1.8k total citations
29 papers, 1.3k citations indexed

About

Mitsuoki Kawano is a scholar working on Molecular Biology, Ecology and Genetics. According to data from OpenAlex, Mitsuoki Kawano has authored 29 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Molecular Biology, 13 papers in Ecology and 13 papers in Genetics. Recurrent topics in Mitsuoki Kawano's work include Bacteriophages and microbial interactions (13 papers), Bacterial Genetics and Biotechnology (12 papers) and RNA and protein synthesis mechanisms (11 papers). Mitsuoki Kawano is often cited by papers focused on Bacteriophages and microbial interactions (13 papers), Bacterial Genetics and Biotechnology (12 papers) and RNA and protein synthesis mechanisms (11 papers). Mitsuoki Kawano collaborates with scholars based in Japan, United States and Hungary. Mitsuoki Kawano's co-authors include Gisela Storz, L. Aravind, Hideya Kawaji, Hiroaki Kasai, Taku Oshima, Hirotada Mori, Yoshihide Hayashizaki, Motoyuki Sugai, Minoo Rassoulzadegan and Piero Carninci and has published in prestigious journals such as Nucleic Acids Research, PLoS ONE and Scientific Reports.

In The Last Decade

Mitsuoki Kawano

29 papers receiving 1.3k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mitsuoki Kawano Japan 15 967 559 490 275 133 29 1.3k
Liron Argaman Israel 16 1.5k 1.5× 893 1.6× 697 1.4× 65 0.2× 104 0.8× 21 1.8k
Fabian Amman Austria 20 1.1k 1.1× 291 0.5× 187 0.4× 146 0.5× 56 0.4× 47 1.4k
Sandrine Chabas France 12 831 0.9× 312 0.6× 311 0.6× 96 0.3× 27 0.2× 15 1.3k
Gregory J. McKenzie United States 12 850 0.9× 618 1.1× 127 0.3× 53 0.2× 128 1.0× 15 1.1k
Yuichi Otsuka Japan 16 499 0.5× 378 0.7× 512 1.0× 33 0.1× 87 0.7× 28 874
Nina Molin Høyland‐Kroghsbo Denmark 9 544 0.6× 194 0.3× 338 0.7× 93 0.3× 71 0.5× 17 735
Antoine Giraud France 10 588 0.6× 522 0.9× 79 0.2× 74 0.3× 128 1.0× 17 1.2k
Don G. Ennis United States 18 794 0.8× 563 1.0× 84 0.2× 119 0.4× 65 0.5× 30 1.1k
Susan K. Amundsen United States 17 811 0.8× 497 0.9× 92 0.2× 44 0.2× 80 0.6× 28 1.1k
C Rayssiguier France 8 885 0.9× 461 0.8× 126 0.3× 113 0.4× 54 0.4× 11 1.1k

Countries citing papers authored by Mitsuoki Kawano

Since Specialization
Citations

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

Fields of papers citing papers by Mitsuoki Kawano

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mitsuoki Kawano

This figure shows the co-authorship network connecting the top 25 collaborators of Mitsuoki Kawano. A scholar is included among the top collaborators of Mitsuoki Kawano 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 Mitsuoki Kawano. Mitsuoki Kawano 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.
Makino, Yuko, et al.. (2021). Development of multiplexing gene silencing system using conditionally induced polycistronic synthetic antisense RNAs in Escherichia coli. Biochemical and Biophysical Research Communications. 556. 163–170. 1 indexed citations
2.
Shiotani, Akiko, Hiroshi Matsumoto, Osamu Handa, et al.. (2021). Comparison of mucosa-associated microbiota in Crohn’s disease patients with and without anti-tumor necrosis factor-α therapy. Journal of Clinical Biochemistry and Nutrition. 70(2). 182–188. 4 indexed citations
3.
Umezu, Tomohiro, Koichi Tsuneyama, Kohsuke Kanekura, et al.. (2020). Comprehensive analysis of liver and blood miRNA in precancerous conditions. Scientific Reports. 10(1). 21766–21766. 11 indexed citations
4.
Saito, Mineki, et al.. (2020). Antimicrobial antisense RNA delivery to F-pili producing multidrug-resistant bacteria via a genetically engineered bacteriophage. Biochemical and Biophysical Research Communications. 530(3). 533–540. 7 indexed citations
5.
Kawano, Mitsuoki, et al.. (2019). Artificial small RNA-mediated growth inhibition in Escherichia coli and Salmonella enterica serovar Typhimurium. Biochemical and Biophysical Research Communications. 521(3). 577–583. 5 indexed citations
6.
Lazzi, Camilla, et al.. (2019). Functional characterization of the type I toxin Lpt from Lactobacillus rhamnosus by fluorescence and atomic force microscopy. Scientific Reports. 9(1). 15208–15208. 12 indexed citations
7.
Sato, Mari, Tomohide Suzuki, Mitsuoki Kawano, & Masato Tamura. (2016). Circulating osteocyte-derived exosomes contain miRNAs which are enriched in exosomes from MLO-Y4 cells. Biomedical Reports. 6(2). 223–231. 59 indexed citations
8.
Takahashi, Masayuki, Reyad A. Elbarbary, Norihiro Watanabe, et al.. (2014). Screening of a heptamer-type sgRNA library for potential therapeutic agents against hematological malignancies. Leukemia Research. 38(7). 808–815. 7 indexed citations
9.
Kawaji, Hideya, Marina Lizio, Masayoshi Itoh, et al.. (2014). Comparison of CAGE and RNA-seq transcriptome profiling using clonally amplified and single-molecule next-generation sequencing. Genome Research. 24(4). 708–717. 68 indexed citations
10.
Kawano, Mitsuoki, et al.. (2013). Correction: Novel Small Noncoding RNAs in Mouse Spermatozoa, Zygotes and Early Embryos. PLoS ONE. 8(5). 1 indexed citations
11.
Kouno, Tsukasa, Michiel de Hoon, Jessica C. Mar, et al.. (2013). Temporal dynamics and transcriptional control using single-cell gene expression analysis. Genome biology. 14(10). R118–R118. 39 indexed citations
12.
Kawano, Mitsuoki, Hideya Kawaji, Valérie Grandjean, Jafar Kiani, & Minoo Rassoulzadegan. (2012). Novel Small Noncoding RNAs in Mouse Spermatozoa, Zygotes and Early Embryos. PLoS ONE. 7(9). e44542–e44542. 96 indexed citations
13.
Kawano, Mitsuoki. (2012). Divergently overlappingcis-encoded antisense RNA regulating toxin-antitoxin systems fromE. coli. RNA Biology. 9(12). 1520–1527. 56 indexed citations
14.
Shinohara, Yoshiaki, Kazuko Yahagi, Mitsuoki Kawano, et al.. (2011). miRNA profiling of bilateral rat hippocampal CA3 by deep sequencing. Biochemical and Biophysical Research Communications. 409(2). 293–298. 14 indexed citations
15.
Hoon, Michiel de, Ryan J. Taft, Takehiro Hashimoto, et al.. (2010). Cross-mapping and the identification of editing sites in mature microRNAs in high-throughput sequencing libraries. Genome Research. 20(2). 257–264. 107 indexed citations
16.
Fozo, Elizabeth M., Mitsuoki Kawano, Fanette Fontaine, et al.. (2008). Repression of small toxic protein synthesis by the Sib and OhsC small RNAs. Molecular Microbiology. 70(5). 1076–1093. 134 indexed citations
17.
Kawano, Mitsuoki, L. Aravind, & Gisela Storz. (2007). An antisense RNA controls synthesis of an SOS‐induced toxin evolved from an antitoxin. Molecular Microbiology. 64(3). 738–754. 205 indexed citations
18.
Kawano, Mitsuoki. (2005). Detection of low-level promoter activity within open reading frame sequences of Escherichia coli. Nucleic Acids Research. 33(19). 6268–6276. 36 indexed citations
19.
20.

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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