Nobuo N. Noda

10.3k total citations · 9 hit papers
127 papers, 7.5k citations indexed

About

Nobuo N. Noda is a scholar working on Epidemiology, Molecular Biology and Cell Biology. According to data from OpenAlex, Nobuo N. Noda has authored 127 papers receiving a total of 7.5k indexed citations (citations by other indexed papers that have themselves been cited), including 79 papers in Epidemiology, 68 papers in Molecular Biology and 47 papers in Cell Biology. Recurrent topics in Nobuo N. Noda's work include Autophagy in Disease and Therapy (79 papers), Endoplasmic Reticulum Stress and Disease (39 papers) and Cellular transport and secretion (14 papers). Nobuo N. Noda is often cited by papers focused on Autophagy in Disease and Therapy (79 papers), Endoplasmic Reticulum Stress and Disease (39 papers) and Cellular transport and secretion (14 papers). Nobuo N. Noda collaborates with scholars based in Japan, China and United States. Nobuo N. Noda's co-authors include Fuyuhiko Inagaki, Yoshinori Ohsumi, Yūko Fujioka, Hitoshi Nakatogawa, Hiroyuki Kumeta, Takao Hanada, Takuo Osawa, Yoshinobu Ichimura, Toshifumi Takao and Yoshinori Satomi and has published in prestigious journals such as Nature, Chemical Reviews and Proceedings of the National Academy of Sciences.

In The Last Decade

Nobuo N. Noda

118 papers receiving 7.5k citations

Hit Papers

The Atg12-Atg5 Conjugate Has a Novel E3-like Activity for... 2007 2026 2013 2019 2007 2010 2008 2019 2009 250 500 750

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Nobuo N. Noda Japan 45 5.2k 3.9k 2.5k 829 635 127 7.5k
Nicholas T. Ktistakis United Kingdom 47 3.8k 0.7× 4.6k 1.2× 3.5k 1.4× 935 1.1× 522 0.8× 100 8.4k
Yūko Fujioka Japan 32 3.3k 0.6× 2.6k 0.7× 1.5k 0.6× 513 0.6× 517 0.8× 55 4.8k
Misuzu Baba Japan 28 3.8k 0.7× 2.7k 0.7× 2.3k 0.9× 499 0.6× 458 0.7× 47 5.1k
Vladimir V. Rogov Russia 32 3.5k 0.7× 3.3k 0.8× 1.3k 0.5× 533 0.6× 189 0.3× 103 6.2k
Yoshinori Satomi Japan 28 2.3k 0.4× 3.9k 1.0× 1.1k 0.4× 319 0.4× 560 0.9× 60 6.3k
Chunaram Choudhary Denmark 52 2.0k 0.4× 12.7k 3.2× 1.6k 0.7× 408 0.5× 467 0.7× 86 16.0k
Mathew E. Sowa United States 40 2.3k 0.4× 9.7k 2.5× 2.4k 1.0× 236 0.3× 405 0.6× 50 12.0k
Maria Antonietta De Matteis Italy 49 1.5k 0.3× 5.9k 1.5× 4.9k 2.0× 1.4k 1.6× 304 0.5× 129 9.5k
Maurizio Molinari Switzerland 48 2.3k 0.4× 5.1k 1.3× 5.1k 2.1× 348 0.4× 296 0.5× 114 9.2k
Jeffrey L. Brodsky United States 68 2.9k 0.6× 10.1k 2.6× 7.4k 3.0× 256 0.3× 919 1.4× 268 15.6k

Countries citing papers authored by Nobuo N. Noda

Since Specialization
Citations

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

Fields of papers citing papers by Nobuo N. Noda

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Nobuo N. Noda. 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 Nobuo N. Noda. The network helps show where Nobuo N. Noda may publish in the future.

Co-authorship network of co-authors of Nobuo N. Noda

This figure shows the co-authorship network connecting the top 25 collaborators of Nobuo N. Noda. A scholar is included among the top collaborators of Nobuo N. Noda 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 Nobuo N. Noda. Nobuo N. Noda 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.
Fujioka, Yūko & Nobuo N. Noda. (2025). Mechanisms of autophagosome formation. Proceedings of the Japan Academy Series B. 101(1). 32–40. 1 indexed citations
2.
Noda, Nobuo N., et al.. (2025). The autophagy protein ATG-9 regulates lysosome function and integrity. The Journal of Cell Biology. 224(6). 4 indexed citations
3.
Sasazawa, Yukiko, Daisuke Noshiro, Mitsuhiro Kitagawa, et al.. (2025). Ubiquilin-2 liquid droplets catalyze α-synuclein fibril formation. The EMBO Journal. 44(22). 6527–6555.
4.
Hama, Yutaro, Yuta Ogasawara, & Nobuo N. Noda. (2023). Autophagy and cancer: Basic mechanisms and inhibitor development. Cancer Science. 114(7). 2699–2708. 26 indexed citations
5.
Ishimura, Ryosuke, et al.. (2023). Mechanistic insights into the roles of the UFM1 E3 ligase complex in ufmylation and ribosome-associated protein quality control. Science Advances. 9(33). eadh3635–eadh3635. 27 indexed citations
6.
Komatsu, Masaaki, Toshifumi Inada, & Nobuo N. Noda. (2023). The UFM1 system: Working principles, cellular functions, and pathophysiology. Molecular Cell. 84(1). 156–169. 26 indexed citations
7.
Ishimura, Ryosuke, Daisuke Noshiro, Yasuko Ono, et al.. (2022). The UFM1 system regulates ER-phagy through the ufmylation of CYB5R3. Nature Communications. 13(1). 7857–7857. 50 indexed citations
8.
Cui, Jin, Yuta Ogasawara, Kazuaki Matoba, et al.. (2022). Targeting the ATG5-ATG16L1 Protein–Protein Interaction with a Hydrocarbon-Stapled Peptide Derived from ATG16L1 for Autophagy Inhibition. Journal of the American Chemical Society. 144(38). 17671–17679. 19 indexed citations
9.
Noda, Nobuo N.. (2021). Atg2 and Atg9: Intermembrane and interleaflet lipid transporters driving autophagy. Biochimica et Biophysica Acta (BBA) - Molecular and Cell Biology of Lipids. 1866(8). 158956–158956. 55 indexed citations
10.
Kodera, Noriyuki, Daisuke Noshiro, Tetsuya Mori, et al.. (2020). Structural and dynamics analysis of intrinsically disordered proteins by high-speed atomic force microscopy. Nature Nanotechnology. 16(2). 181–189. 74 indexed citations
11.
Noda, Hidetoshi, Tatsuro Maruyama, Naoki Takizawa, et al.. (2019). A C4N4 Diaminopyrimidine Fluorophore. Chemistry - A European Journal. 25(17). 4299–4304. 2 indexed citations
12.
Yamano, Koji, Chunxin Wang, Shireen A. Sarraf, et al.. (2018). Endosomal Rab cycles regulate Parkin-mediated mitophagy. eLife. 7. 127 indexed citations
13.
Yamasaki, Akinori & Nobuo N. Noda. (2017). Structural Biology of the Cvt Pathway. Journal of Molecular Biology. 429(4). 531–542. 22 indexed citations
14.
Tamura, Naoki, et al.. (2013). Atg18 phosphoregulation controls organellar dynamics by modulating its phosphoinositide-binding activity. The Journal of Cell Biology. 202(4). 685–698. 40 indexed citations
15.
Noda, Nobuo N., Yasuyuki Ikegami, & Haruo Uehara. (2002). Extraction Condition of OTEC Using the Uehara Cycle. 8 indexed citations
16.
Kouno, Hiroaki, et al.. (1998). Meson-Nucleon Vertex Corrections in the Cutoff Field Theory and Tensor Coupling. Progress of Theoretical Physics. 99(3). 395–411.
17.
Noda, Nobuo N., et al.. (1993). A Case of Plasmacytoma Arising from the Mandible. The Journal of the Kyushu Dental Society. 47(1). 297–303. 1 indexed citations
18.
Noda, Nobuo N.. (1960). Studies on Solvent Extraction Using Radioactive Isotope. VII. Solvent Extraction of Antimony?Hydrochloric Acid System. Nippon kagaku zassi. 81(3). 437–440. 2 indexed citations
20.
Noda, Nobuo N. & Hiroyuki Yoshida. (1959). Studies on the Solvent Extraction Using Radioactive Isotope. IV. Some Informations on Solvent Extraction of Cobalt a-Nitroso-P-naphtholate Complex.. Nippon kagaku zassi. 80(9). 1008–1011. 4 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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