Toshihide Kobayashi
- Cell Biology top 0.2%
- Cellular transport and secretion 45
- Molecular Biology top 0.5%
- Lipid Membrane Structure and Behavior 122
- Sphingolipid Metabolism and Signaling 61
- RNA Interference and Gene Delivery 10
- Physiology top 0.5%
- Erythrocyte Function and Pathophysiology 41
- Lysosomal Storage Disorders Research 15
- Physiology top 1%
- Erythrocyte Function and Pathophysiology 41
- Lysosomal Storage Disorders Research 15
- Biochemistry top 0.5%
- Lipid metabolism and biosynthesis 14
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- Force Microscopy Techniques and Applications 10
- Co-authors
- Jean GrüenbergRobert G. PartonAsami MakinoFrançoise Hullin‐MatsudaMotohide MuratePhilippe de MoerlooseEspen StangReiko Ishitsuka
- Partner nations
- JapanFranceUnited States
In The Last Decade
Toshihide Kobayashi
230 papers receiving 11.6k citations
Hit Papers
Peers
Comparison fields: 5 of 150
- Cell Biology 3.0k
- Molecular Biology 8.3k
- Physiology 386
- Physiology 2.1k
- Biochemistry 576
Countries citing papers authored by Toshihide Kobayashi
This map shows the geographic impact of Toshihide Kobayashi'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 Toshihide Kobayashi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Toshihide Kobayashi more than expected).
Fields of papers citing papers by Toshihide Kobayashi
This network shows the impact of papers produced by Toshihide Kobayashi. 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 Toshihide Kobayashi. The network helps show where Toshihide Kobayashi may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Toshihide Kobayashi, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2024 | 4 | |
| 2 | 2024 | 1 | |
| 3 | 2023 | 2 | |
| 4 | 2023 | 2 | |
| 5 | 2023 | 9 | |
| 6 | 2022 | 22 | |
| 7 | 2019 | 54 | |
| 8 | 2017 | 202 | |
| 9 | 2016 | 8 | |
| 10 | 2013 | 257 | |
| 11 | 2013 | 45 | |
| 12 | 2012 | 121 | |
| 13 | 2011 | 34 | |
| 14 | 2010 | 1 | |
| 15 | 2009 | 156 | |
| 16 | 2007 | 2 | |
| 17 | 2006 | 21 | |
| 18 | 2004 | 82 | |
| 19 | 2002 | 65 | |
| 20 | 1993 | 216 |
About Toshihide Kobayashi
Toshihide Kobayashi is a scholar working on Cell Biology, Molecular Biology and Physiology, having authored 234 papers that have together received 11.7k indexed citations. Recurring topics across this work include Lipid Membrane Structure and Behavior (122 papers), Sphingolipid Metabolism and Signaling (61 papers), Cellular transport and secretion (45 papers), Erythrocyte Function and Pathophysiology (41 papers), Lysosomal Storage Disorders Research (15 papers), Lipid metabolism and biosynthesis (14 papers), Force Microscopy Techniques and Applications (10 papers) and RNA Interference and Gene Delivery (10 papers). The work is most often cited by research in Cell Biology (3.0k citations), Molecular Biology (8.3k citations) and Physiology (386 citations). Toshihide Kobayashi has collaborated with scholars based in Japan, France and United States. Frequent co-authors include Jean Grüenberg, Robert G. Parton, Asami Makino, Françoise Hullin‐Matsuda, Motohide Murate, Philippe de Moerloose, Espen Stang, Reiko Ishitsuka, Tomoko Koumura and Masato Umeda. Their work appears in journals such as Nature, Cell and Proceedings of the National Academy of Sciences.
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.