Yoshimi Nakagawa
About
Yoshimi Nakagawa is a scholar working on Molecular Biology, Surgery and Epidemiology.
According to data from OpenAlex, Yoshimi Nakagawa has authored 94 papers receiving a total of 4.8k indexed citations (citations by other indexed papers that have themselves been cited), including 60 papers in Molecular Biology, 32 papers in Surgery and 20 papers in Epidemiology. Recurrent topics in Yoshimi Nakagawa's work include Cholesterol and Lipid Metabolism (24 papers), Peroxisome Proliferator-Activated Receptors (22 papers) and Metabolism, Diabetes, and Cancer (11 papers). Yoshimi Nakagawa is often cited by papers focused on Cholesterol and Lipid Metabolism (24 papers), Peroxisome Proliferator-Activated Receptors (22 papers) and Metabolism, Diabetes, and Cancer (11 papers). Yoshimi Nakagawa collaborates with scholars based in Japan, United States and Germany. Yoshimi Nakagawa's co-authors include Hitoshi Shimano, Takashi Matsuzaka, Nobuhiro Yamada, Naoya Yahagi, Hiroaki Suzuki, Akimitsu Takahashi, Hirohito Sone, Hideo Toyoshima, Takashi Yamamoto and Motohiro Sekiya and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Nature Medicine.
In The Last Decade
Yoshimi Nakagawa
92 papers receiving 4.7k citations
Hit Papers
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late) cites · hero ref
| Name | h | Career | Trend | Papers | Cites | |||||
|---|---|---|---|---|---|---|---|---|---|---|
| Yoshimi Nakagawa Japan | 36 | 2.7k | 1.2k | 1.1k | 1.1k | 852 | 94 | 4.8k | ||
| Jongsook Kim Kemper United States | 40 | 2.5k 0.9× | 1.1k 0.9× | 1.7k 1.5× | 1.0k 0.9× | 998 1.2× | 66 | 5.3k | ||
| John C. Yoon United States | 14 | 3.6k 1.3× | 900 0.7× | 844 0.8× | 791 0.7× | 2.1k 2.4× | 21 | 5.5k | ||
| Haiming Cao United States | 22 | 2.2k 0.8× | 449 0.4× | 1.2k 1.1× | 828 0.8× | 1.4k 1.6× | 40 | 4.3k | ||
| Andrew N. Billin United States | 38 | 3.7k 1.4× | 767 0.6× | 810 0.7× | 588 0.6× | 588 0.7× | 77 | 5.2k | ||
| David L. Silver United States | 40 | 3.7k 1.4× | 2.5k 2.0× | 768 0.7× | 709 0.7× | 1.1k 1.3× | 80 | 6.7k | ||
| Jichun Yang China | 37 | 3.0k 1.1× | 863 0.7× | 517 0.5× | 1.8k 1.7× | 699 0.8× | 115 | 5.1k | ||
| Trey Coleman United States | 30 | 2.0k 0.8× | 761 0.6× | 955 0.9× | 434 0.4× | 1.6k 1.8× | 42 | 4.0k | ||
| Murielle M. Véniant United States | 44 | 3.7k 1.4× | 1.4k 1.2× | 961 0.9× | 469 0.4× | 1.2k 1.4× | 95 | 6.5k | ||
| Dietbert Neumann Netherlands | 34 | 4.8k 1.8× | 2.0k 1.7× | 816 0.7× | 607 0.6× | 1.1k 1.3× | 83 | 6.0k | ||
| Yoko Iizuka Japan | 32 | 3.1k 1.1× | 2.2k 1.8× | 1.1k 1.0× | 1.0k 0.9× | 1.1k 1.3× | 65 | 5.9k |
Countries citing papers authored by Yoshimi Nakagawa
Since
Specialization
Citations
This map shows the geographic impact of Yoshimi Nakagawa'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 Yoshimi Nakagawa with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yoshimi Nakagawa more than expected).
Fields of papers citing papers by Yoshimi Nakagawa
Since
Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences
This network shows the impact of papers produced by Yoshimi Nakagawa. 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 Yoshimi Nakagawa. The network helps show where Yoshimi Nakagawa may publish in the future.
Co-authorship network of co-authors of Yoshimi Nakagawa
This figure shows the co-authorship network connecting the top 25 collaborators of Yoshimi Nakagawa. A scholar is included among the top collaborators of Yoshimi Nakagawa 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 Yoshimi Nakagawa. Yoshimi Nakagawa is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
1.
Kodama, Satoru, Yoko Yachi, Chika Horikawa, et al.. (2025). Relationship Between Improvements in Glycemic Control and Risk of Pregnancy Complications in Patients With Diabetes Mellitus: Metaregression Analysis of Randomized Controlled Trials of Intensive Glucose Management. Journal of Diabetes Research. 2025(1). 3490884–3490884.
2.
Nozaki, Yuka, Masaki Kobayashi, Yuhei Mizunoe, et al.. (2025). Mipep deficiency in adipocytes impairs mitochondrial protein maturation and leads to systemic inflammation and metabolic dysfunctions. Scientific Reports. 15(1). 12839–12839.
3.
Oishi, Yumiko, Hiroyuki Koike, Yoshimi Nakagawa, et al.. (2024). Macrophage SREBP1 regulates skeletal muscle regeneration. Frontiers in Immunology. 14. 1251784–1251784.
4.
Iyoda, Takuya, Yunong Wang, Naoyuki Okita, et al.. (2024). Bioactive TNIIIA2 Sequence in Tenascin-C Is Responsible for Macrophage Foam Cell Transformation; Potential of FNIII14 Peptide Derived from Fibronectin in Suppression of Atherosclerotic Plaque Formation. International Journal of Molecular Sciences. 25(3). 1825–1825.
5.
Cao, Ye, Yoshimi Nakagawa, Anne‐Marie Lundsgaard, et al.. (2024). Dietary medium-chain fatty acids reduce hepatic fat accumulation via activation of a CREBH-FGF21 axis. Molecular Metabolism. 87. 101991–101991.
6.
Kim, Jun‐Dal, et al.. (2023). Increased angiotensin II coupled with decreased Adra1a expression enhances cardiac hypertrophy in pregnancy-associated hypertensive mice. Journal of Biological Chemistry. 299(3). 102964–102964.
7.
Kodama, Satoru, Kazuya Fujihara, Chika Horikawa, et al.. (2021). Predictive ability of current machine learning algorithms for type 2 diabetes mellitus: A meta‐analysis. Journal of Diabetes Investigation. 13(5). 900–908.
8.
Fujihara, Kazuya, Kenji Saito, Chika Horikawa, et al.. (2021). Carrot Consumption Frequency Associated with Reduced BMI and Obesity through the SNP Intermediary rs4445711. Nutrients. 13(10). 3478–3478.
9.
Fujihara, Kazuya, MAYUKO H. YAMADA, Masahiko Yamamoto, et al.. (2020). Severity of Hypertension as a Predictor of Initiation of Dialysis among Study Participants with and without Diabetes Mellitus. Journal of Investigative Medicine. 69(3). 724–729.
10.
Sugasawa, Takehito, et al.. (2018). Influence of acute exercise on renalase and its regulatory mechanism. Life Sciences. 210. 235–242.
11.
Nakagawa, Yoshimi, Yunong Wang, Song‐iee Han, et al.. (2017). Effects of K-877, a novel selective PPARα modulator, on small intestine contribute to the amelioration of hyperlipidemia in low-density lipoprotein receptor knockout mice. Journal of Pharmacological Sciences. 133(4). 214–222.
12.
Han, Song‐iee, Yuki Murayama, Aoi Satoh, et al.. (2017). Selective peroxisome proliferator‐activated receptor‐α modulator K‐877 efficiently activates the peroxisome proliferator‐activated receptor‐α pathway and improves lipid metabolism in mice. Journal of Diabetes Investigation. 8(4). 446–452.
13.
Shimada, Masako, Takashi Matsuzaka, Kiyo‐aki Ishii, et al.. (2016). Crucial Role of Elovl6 in Chondrocyte Growth and Differentiation during Growth Plate Development in Mice. PLoS ONE. 11(7). e0159375–e0159375.
14.
Osaki, Yoshinori, Yoshimi Nakagawa, Hitoshi Iwasaki, et al.. (2015). Skeletal muscle-specific HMG-CoA reductase knockout mice exhibit rhabdomyolysis: A model for statin-induced myopathy. Biochemical and Biophysical Research Communications. 466(3). 536–540.
15.
Naka, A., Kaoruko Iida, Yoshimi Nakagawa, et al.. (2012). TFE3 inhibits myoblast differentiation in C2C12 cells via down-regulating gene expression of myogenin. Biochemical and Biophysical Research Communications. 430(2). 664–669.
16.
Kumadaki, Shin, Tadayoshi Karasawa, Takashi Matsuzaka, et al.. (2011). Inhibition of Ubiquitin Ligase F-box and WD Repeat Domain-containing 7α (Fbw7α) Causes Hepatosteatosis through Krüppel-like Factor 5 (KLF5)/Peroxisome Proliferator-activated Receptor γ2 (PPARγ2) Pathway but Not SREBP-1c Protein in Mice. Journal of Biological Chemistry. 286(47). 40835–40846.
17.
Shimizu, Hidehisa, et al.. (2010). Protein tyrosine phosphatase PTPεM negatively regulates PDGF β-receptor signaling induced by high glucose and PDGF in vascular smooth muscle cells. American Journal of Physiology-Cell Physiology. 299(5). C1144–C1152.
18.
Ishikawa, Mayumi, Yuko Iwasaki, Shigeru Yatoh, et al.. (2008). Cholesterol accumulation and diabetes in pancreatic β-cell-specific SREBP-2 transgenic mice: a new model for lipotoxicity. Journal of Lipid Research. 49(12). 2524–2534.
19.
Nakagawa, Yoshimi, Naohito Aoki, Koji Aoyama, et al.. (2005). Receptor-Type Protein Tyrosine Phosphatase ε (PTPεM) is a Negative Regulator of Insulin Signaling in Primary Hepatocytes and Liver. ZOOLOGICAL SCIENCE. 22(2). 169–175.
20.
Najima, Yuho, Naoya Yahagi, Yoshinori Takeuchi, et al.. (2005). High Mobility Group Protein-B1 Interacts with Sterol Regulatory Element-binding Proteins to Enhance Their DNA Binding. Journal of Biological Chemistry. 280(30). 27523–27532.
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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