Taki Nishimura

41 total papers · 2.9k total citations
27 papers, 1.8k citations indexed

About

Taki Nishimura is a scholar working on Cell Biology, Epidemiology and Molecular Biology. According to data from OpenAlex, Taki Nishimura has authored 27 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Cell Biology, 18 papers in Epidemiology and 9 papers in Molecular Biology. Recurrent topics in Taki Nishimura's work include Autophagy in Disease and Therapy (18 papers), Cellular transport and secretion (12 papers) and Endoplasmic Reticulum Stress and Disease (7 papers). Taki Nishimura is often cited by papers focused on Autophagy in Disease and Therapy (18 papers), Cellular transport and secretion (12 papers) and Endoplasmic Reticulum Stress and Disease (7 papers). Taki Nishimura collaborates with scholars based in Japan, United Kingdom and Germany. Taki Nishimura's co-authors include Noboru Mizushima, Sharon A. Tooze, Yuriko Sakamaki, Anoop Kumar G. Velikkakath, Naotada Ishihara, Tohru Natsume, Peidu Jiang, Eisuke Itakura, Tomohisa Hatta and Hiroyuki Arai and has published in prestigious journals such as Proceedings of the National Academy of Sciences, The EMBO Journal and Molecular Cell.

In The Last Decade

Taki Nishimura

25 papers receiving 1.8k citations

Hit Papers

The HOPS complex mediates... 2014 2026 2018 2022 2014 2020 100 200 300

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Taki Nishimura 1.2k 755 745 292 241 27 1.8k
Christopher A. Lamb 1.3k 1.1× 840 1.1× 841 1.1× 294 1.0× 288 1.2× 23 2.1k
Keisuke Tabata 1.5k 1.3× 745 1.0× 570 0.8× 280 1.0× 231 1.0× 30 2.2k
Chao-Wen Wang 1.1k 0.9× 1.2k 1.6× 990 1.3× 185 0.6× 208 0.9× 30 2.2k
Bindi Patel 1.1k 0.9× 1.1k 1.4× 503 0.7× 224 0.8× 268 1.1× 25 2.1k
Damián Gatica 1.1k 1.0× 1.0k 1.3× 662 0.9× 163 0.6× 239 1.0× 21 2.0k
Prasanna Satpute‐Krishnan 883 0.7× 1.0k 1.3× 633 0.8× 128 0.4× 305 1.3× 13 1.8k
Mariella Vicinanza 1.1k 0.9× 1.2k 1.6× 973 1.3× 332 1.1× 385 1.6× 23 2.4k
Orane Visvikis 823 0.7× 958 1.3× 365 0.5× 194 0.7× 278 1.2× 20 1.9k
Hong Zhang 960 0.8× 880 1.2× 479 0.6× 231 0.8× 224 0.9× 27 1.8k
Hideaki Morishita 1.2k 1.0× 960 1.3× 454 0.6× 233 0.8× 158 0.7× 37 2.0k

Countries citing papers authored by Taki Nishimura

Since Specialization
Citations

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

Fields of papers citing papers by Taki Nishimura

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Taki Nishimura

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

All Works

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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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