Akito Takamura

4.5k total citations · 3 hit papers
13 papers, 3.6k citations indexed

About

Akito Takamura is a scholar working on Epidemiology, Molecular Biology and Rheumatology. According to data from OpenAlex, Akito Takamura has authored 13 papers receiving a total of 3.6k indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Epidemiology, 4 papers in Molecular Biology and 4 papers in Rheumatology. Recurrent topics in Akito Takamura's work include Inflammatory Myopathies and Dermatomyositis (4 papers), Rheumatoid Arthritis Research and Therapies (4 papers) and Autophagy in Disease and Therapy (3 papers). Akito Takamura is often cited by papers focused on Inflammatory Myopathies and Dermatomyositis (4 papers), Rheumatoid Arthritis Research and Therapies (4 papers) and Autophagy in Disease and Therapy (3 papers). Akito Takamura collaborates with scholars based in Japan and United States. Akito Takamura's co-authors include Taichi Hara, Noboru Mizushima, Chieko Kishi, Tohru Natsume, Jun‐Lin Guan, Shun-ichiro Iemura, Naoyuki Yamada, Yutaka Miura, Kenji Takehana and Noriko Oshiro and has published in prestigious journals such as Genes & Development, The Journal of Cell Biology and Molecular Biology of the Cell.

In The Last Decade

Akito Takamura

13 papers receiving 3.5k citations

Hit Papers

Nutrient-dependent mTORC1... 2008 2026 2014 2020 2009 2011 2008 500 1000 1.5k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Akito Takamura Japan 10 2.8k 1.8k 821 464 365 13 3.6k
Neil Otto United States 8 2.7k 1.0× 2.1k 1.1× 759 0.9× 456 1.0× 346 0.9× 13 4.0k
Chang Hwa Jung United States 8 2.9k 1.0× 2.2k 1.2× 818 1.0× 496 1.1× 360 1.0× 9 4.2k
Maria Perander Norway 17 2.2k 0.8× 2.1k 1.2× 804 1.0× 291 0.6× 207 0.6× 20 3.7k
Ezgi Tasdemir France 16 2.1k 0.7× 1.9k 1.0× 538 0.7× 318 0.7× 275 0.8× 16 3.4k
Ivana Novak Croatia 19 2.6k 0.9× 2.6k 1.4× 887 1.1× 334 0.7× 198 0.5× 28 4.3k
Edmond Y.W. Chan United Kingdom 17 2.2k 0.8× 1.3k 0.7× 932 1.1× 467 1.0× 203 0.6× 19 2.9k
Francesca Nazio Italy 25 2.0k 0.7× 1.8k 1.0× 552 0.7× 239 0.5× 180 0.5× 38 3.1k
Hai‐Xin Yuan China 22 1.8k 0.6× 2.8k 1.5× 2.0k 2.4× 299 0.6× 214 0.6× 45 5.0k
Kenneth Bowitz Larsen Norway 16 1.9k 0.7× 1.6k 0.9× 740 0.9× 282 0.6× 208 0.6× 22 2.9k
Carla F. Bento United Kingdom 21 1.6k 0.6× 1.2k 0.7× 893 1.1× 278 0.6× 159 0.4× 28 3.0k

Countries citing papers authored by Akito Takamura

Since Specialization
Citations

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

Fields of papers citing papers by Akito Takamura

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Akito Takamura

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

All Works

13 of 13 papers shown
2.
Kamiya, Mari, Fumitaka Mizoguchi, Akito Takamura, et al.. (2019). A new in vitro model of polymyositis reveals CD8+ T cell invasion into muscle cells and its cytotoxic role. Lara D. Veeken. 59(1). 224–232. 16 indexed citations
4.
Sasaki, Hirokazu, Akito Takamura, Kimito Kawahata, et al.. (2018). Peripheral blood lymphocyte subset repertoires are biased and reflect clinical features in patients with dermatomyositis. Scandinavian Journal of Rheumatology. 48(3). 225–229. 11 indexed citations
5.
Ota, Mineto, et al.. (2016). Anti-EJ antibody positive interstitial lung disease with skin changes at the fingertips. Japanese Journal of Clinical Immunology. 39(2). 150–153. 5 indexed citations
10.
Takamura, Akito, Masaaki Komatsu, Taichi Hara, et al.. (2011). Autophagy-deficient mice develop multiple liver tumors. Genes & Development. 25(8). 795–800. 1066 indexed citations breakdown →
11.
Hara, Taichi, Takeshi Kaizuka, Chieko Kishi, et al.. (2009). Nutrient-dependent mTORC1 Association with the ULK1–Atg13–FIP200 Complex Required for Autophagy. Molecular Biology of the Cell. 20(7). 1981–1991. 1642 indexed citations breakdown →
12.
Hara, Taichi, Akito Takamura, Chieko Kishi, et al.. (2008). FIP200, a ULK-interacting protein, is required for autophagosome formation in mammalian cells. The Journal of Cell Biology. 181(3). 497–510. 783 indexed citations breakdown →
13.
Moriwaki, Hisataka, Akito Takamura, Kazuo Nagura, et al.. (1988). [Systematized therapeutic intervention in intrahepatic cholestasis, with special reference to ursodeoxycholic acid therapy of corticosteroid non-effective cases].. PubMed. 85(11). 2420–9. 1 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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