Yoshio Kodera

1.9k total citations
73 papers, 1.4k citations indexed

About

Yoshio Kodera is a scholar working on Molecular Biology, Spectroscopy and Oncology. According to data from OpenAlex, Yoshio Kodera has authored 73 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 45 papers in Molecular Biology, 30 papers in Spectroscopy and 7 papers in Oncology. Recurrent topics in Yoshio Kodera's work include Advanced Proteomics Techniques and Applications (29 papers), Mass Spectrometry Techniques and Applications (19 papers) and Metabolomics and Mass Spectrometry Studies (12 papers). Yoshio Kodera is often cited by papers focused on Advanced Proteomics Techniques and Applications (29 papers), Mass Spectrometry Techniques and Applications (19 papers) and Metabolomics and Mass Spectrometry Studies (12 papers). Yoshio Kodera collaborates with scholars based in Japan, United States and India. Yoshio Kodera's co-authors include Yusuke Kawashima, Fumio Nomura, Takeshi Tomonaga, Tadakazu Maeda, Mamoru Satoh, Kazuyuki Matsushita, Masamichi Ohishi, Kazuyuki Sogawa, Masayoshi Shichiri and Hiroyuki Matsumoto and has published in prestigious journals such as Nucleic Acids Research, Nature Communications and PLoS ONE.

In The Last Decade

Yoshio Kodera

69 papers receiving 1.4k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Yoshio Kodera Japan 21 824 375 201 160 132 73 1.4k
Yusuke Kawashima Japan 22 653 0.8× 302 0.8× 168 0.8× 134 0.8× 81 0.6× 86 1.4k
Jir̆ı́ Petrák Czechia 25 989 1.2× 178 0.5× 138 0.7× 124 0.8× 128 1.0× 61 2.0k
Kyunggon Kim South Korea 24 961 1.2× 231 0.6× 143 0.7× 155 1.0× 115 0.9× 94 1.6k
Harmjan R. Vos Netherlands 24 1.3k 1.6× 150 0.4× 252 1.3× 188 1.2× 120 0.9× 58 1.8k
Fredrik Edfors Sweden 17 780 0.9× 238 0.6× 82 0.4× 82 0.5× 55 0.4× 40 1.2k
Bei Zhen China 17 645 0.8× 86 0.2× 129 0.6× 123 0.8× 156 1.2× 21 1.2k
Arjen Scholten Netherlands 25 1.3k 1.6× 361 1.0× 219 1.1× 64 0.4× 139 1.1× 54 1.9k
G Salvatore Italy 25 520 0.6× 114 0.3× 112 0.6× 54 0.3× 186 1.4× 57 1.4k
Alessandra Olianas Italy 17 366 0.4× 141 0.4× 48 0.2× 27 0.2× 118 0.9× 70 991
Daniel Vyoral Czechia 19 510 0.6× 108 0.3× 55 0.3× 73 0.5× 124 0.9× 33 1.2k

Countries citing papers authored by Yoshio Kodera

Since Specialization
Citations

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

Fields of papers citing papers by Yoshio Kodera

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yoshio Kodera

This figure shows the co-authorship network connecting the top 25 collaborators of Yoshio Kodera. A scholar is included among the top collaborators of Yoshio Kodera 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 Yoshio Kodera. Yoshio Kodera 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.
Matsui, Takashi, et al.. (2025). Reducing offsite modifications using 2-mercaptoethanol for LC-MS analyses. Biochemical and Biophysical Research Communications. 753. 151485–151485.
2.
Fukushima, Kensuke, Takashi Matsui, Yoshio Kodera, et al.. (2024). Fibrocyte Phenotype of ENTPD1+CD55+ Cells and Its Association with Pain in Osteoarthritic Synovium. International Journal of Molecular Sciences. 25(7). 4085–4085. 3 indexed citations
3.
Okuda, Shujiro, Akiyasu C. Yoshizawa, Daiki Kobayashi, et al.. (2024). jPOST environment accelerates the reuse and reanalysis of public proteome mass spectrometry data. Nucleic Acids Research. 53(D1). D462–D467. 15 indexed citations
4.
Kodera, Yoshio, Masashi Satoh, Takashi Matsui, et al.. (2023). CD39+CD55− Fb Subset Exhibits Myofibroblast-Like Phenotype and Is Associated with Pain in Osteoarthritis of the Knee. Biomedicines. 11(11). 3047–3047. 8 indexed citations
5.
Masubuchi, Nami, Pamela J. Focia, Takashi Matsui, et al.. (2022). A marine sponge-derived lectin reveals hidden pathway for thrombopoietin receptor activation. Nature Communications. 13(1).
6.
Sato, Toshiya, Rika Kato, Saori Yamamori, et al.. (2022). Importance of the Q/N-rich segment for protein stability of endogenous mouse TDP-43. Scientific Reports. 12(1). 14923–14923. 1 indexed citations
7.
Sekita, Yoichi, Yuki Sugiura, Yuki Kawasaki, et al.. (2021). AKT signaling is associated with epigenetic reprogramming via the upregulation of TET and its cofactor, alpha-ketoglutarate during iPSC generation. Stem Cell Research & Therapy. 12(1). 510–510. 14 indexed citations
8.
Fujimoto, Kazumi, et al.. (2021). Circulating prorenin: its molecular forms and plasma concentrations. Hypertension Research. 44(6). 674–684. 4 indexed citations
9.
Kodera, Yoshio, et al.. (2021). GIP_HUMAN[22–51] is a new proatherogenic peptide identified by native plasma peptidomics. Scientific Reports. 11(1). 14470–14470. 6 indexed citations
10.
Takemori, Ayako, Jun Ishizaki, Kenji Nakashima, et al.. (2020). BAC-DROP: Rapid Digestion of Proteome Fractionated via Dissolvable Polyacrylamide Gel Electrophoresis and Its Application to Bottom-Up Proteomics Workflow. Journal of Proteome Research. 20(3). 1535–1543. 19 indexed citations
11.
Fujitani, Kazuko, Asako Otomo, Taro Tachibana, et al.. (2020). PACT/PRKRA and p53 regulate transcriptional activity of DMRT1. Genetics and Molecular Biology. 43(2). e20190017–e20190017. 7 indexed citations
12.
Kodera, Yoshio, et al.. (2020). Oxidised Met147 of human serum albumin is a biomarker of oxidative stress, reflecting glycaemic fluctuations and hypoglycaemia in diabetes. Scientific Reports. 10(1). 268–268. 22 indexed citations
13.
Suzuki, Satoko, Yoshio Kodera, Tatsuya Saito, et al.. (2016). Methionine sulfoxides in serum proteins as potential clinical biomarkers of oxidative stress. Scientific Reports. 6(1). 38299–38299. 60 indexed citations
14.
Mizusawa, Kanta, Yusuke Kawashima, Akie Hamamoto, et al.. (2014). Involvement of melanin-concentrating hormone 2 in background color adaptation of barfin flounder Verasper moseri. General and Comparative Endocrinology. 214. 140–148. 11 indexed citations
15.
16.
Sogawa, Kazuyuki, Yoshio Kodera, Mamoru Satoh, et al.. (2010). Increased Serum Levels of Pigment Epithelium-Derived Factor by Excessive Alcohol Consumption-Detection and Identification by a Three-Step Serum Proteome Analysis. Alcoholism Clinical and Experimental Research. 35(2). 211–217. 19 indexed citations
17.
Iwamura, Masatsugu, Yoshio Kodera, Yusuke Kawashima, et al.. (2010). Profilin 1 overexpression in renal cell carcinoma. International Journal of Urology. 18(1). 63–71. 27 indexed citations
18.
19.
Ohishi, Masamichi, Yoshio Kodera, Sen-ichi FURUDATE, & Tadakazu Maeda. (2008). Disease proteomics of endocrine disorders revealed by two‐dimensional gel electrophoresis and mass spectrometry. PROTEOMICS - CLINICAL APPLICATIONS. 2(3). 327–337.
20.
Kuruma, Hidetoshi, Shinichi Egawa, Masamichi Ohishi, et al.. (2005). High molecular mass proteome of androgen‐independent prostate cancer. PROTEOMICS. 5(4). 1097–1112. 30 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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