Ran Uchitomi

590 total citations
10 papers, 428 citations indexed

About

Ran Uchitomi is a scholar working on Physiology, Molecular Biology and Cell Biology. According to data from OpenAlex, Ran Uchitomi has authored 10 papers receiving a total of 428 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Physiology, 4 papers in Molecular Biology and 4 papers in Cell Biology. Recurrent topics in Ran Uchitomi's work include Adipose Tissue and Metabolism (8 papers), Muscle metabolism and nutrition (4 papers) and Muscle Physiology and Disorders (2 papers). Ran Uchitomi is often cited by papers focused on Adipose Tissue and Metabolism (8 papers), Muscle metabolism and nutrition (4 papers) and Muscle Physiology and Disorders (2 papers). Ran Uchitomi collaborates with scholars based in Japan. Ran Uchitomi's co-authors include Yasutomi Kamei, Yukino Hatazawa, Shinji Miura, Takahiko Shimizu, Nanami Senoo, Yusuke Ono, Mariko Fujita, Kiyoshi Yoshioka and Takumi Sugimoto and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and FEBS Letters.

In The Last Decade

Ran Uchitomi

9 papers receiving 424 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Ran Uchitomi Japan	6	275	161	129	42	37	10	428
Stephen P. Ashcroft United Kingdom	11	255 0.9×	119 0.7×	103 0.8×	32 0.8×	60 1.6×	15	430
Yukino Hatazawa Japan	12	392 1.4×	333 2.1×	215 1.7×	60 1.4×	30 0.8×	19	618
Flavia Bruttini Italy	2	213 0.8×	223 1.4×	117 0.9×	45 1.1×	15 0.4×	3	433
Heather L. Petrick Canada	13	272 1.0×	126 0.8×	136 1.1×	36 0.9×	13 0.4×	29	433
Paulette Rousset France	14	453 1.6×	217 1.3×	230 1.8×	52 1.2×	25 0.7×	24	663
Bruno Gonzaga Teodoro Brazil	12	203 0.7×	173 1.1×	73 0.6×	68 1.6×	14 0.4×	23	435
Ayhan Korkmaz Finland	13	129 0.5×	142 0.9×	56 0.4×	52 1.2×	37 1.0×	22	398
Greg C. Smith Australia	15	225 0.8×	208 1.3×	101 0.8×	62 1.5×	15 0.4×	25	595
Andreina Alfieri Italy	13	119 0.4×	161 1.0×	75 0.6×	45 1.1×	13 0.4×	27	501
N.K. Edens United States	7	303 1.1×	98 0.6×	82 0.6×	92 2.2×	20 0.5×	12	449

Countries citing papers authored by Ran Uchitomi

Since Specialization

Citations

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

Fields of papers citing papers by Ran Uchitomi

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ran Uchitomi

This figure shows the co-authorship network connecting the top 25 collaborators of Ran Uchitomi. A scholar is included among the top collaborators of Ran Uchitomi 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 Ran Uchitomi. Ran Uchitomi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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10 of 10 papers shown

1.

Sugimoto, Takumi, et al.. (2022). A combination of exercise and calorie restriction improves the development of obesity-related type 2 diabetes mellitus in KKAy mice. Bioscience Biotechnology and Biochemistry. 87(1). 108–113.

2.

Uchitomi, Ran, et al.. (2022). Vitamin D Activates Various Gene Expressions, Including Lipid Metabolism, in C2C12 Cells. Journal of Nutritional Science and Vitaminology. 68(1). 65–72. 1 indexed citations

3.

Sugimoto, Takumi, Ran Uchitomi, Yukino Hatazawa, Shinji Miura, & Yasutomi Kamei. (2021). Metabolomic analysis on blood of transgenic mice overexpressing PGC-1α in skeletal muscle. Bioscience Biotechnology and Biochemistry. 85(3). 579–586. 7 indexed citations

4.

Uchitomi, Ran, et al.. (2020). Vitamin D and Sarcopenia: Potential of Vitamin D Supplementation in Sarcopenia Prevention and Treatment. Nutrients. 12(10). 3189–3189. 128 indexed citations

5.

Kamei, Yasutomi, et al.. (2020). Regulation of Skeletal Muscle Function by Amino Acids. Nutrients. 12(1). 261–261. 168 indexed citations

6.

Uchitomi, Ran, et al.. (2019). Screening dataset of food components that enhance transcriptional activity of PGC1-beta. SHILAP Revista de lepidopterología. 23. 103814–103814. 2 indexed citations

7.

Uchitomi, Ran, Yukino Hatazawa, Nanami Senoo, et al.. (2019). Metabolomic Analysis of Skeletal Muscle in Aged Mice. Scientific Reports. 9(1). 10425–10425. 94 indexed citations

8.

Uchitomi, Ran, et al.. (2019). Metabolomic analysis of C2C12 myoblasts induced by the transcription factorFOXO1. FEBS Letters. 593(12). 1303–1312. 5 indexed citations

9.

Uchitomi, Ran, et al.. (2018). Genistein, daidzein, and resveratrols stimulate PGC-1β-mediated gene expression. Biochemistry and Biophysics Reports. 17. 51–55. 15 indexed citations

10.

Uchitomi, Ran, et al.. (2018). Effects of long-term physical exercise on skeletal muscles in senescence-accelerated mice (SAMP8). Bioscience Biotechnology and Biochemistry. 83(3). 518–524. 8 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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