Daiki Kobayashi
- Molecular Biology top 10%
- Metabolomics and Mass Spectrometry Studies 3
- Ubiquitin and proteasome pathways 3
- Genomics and Phylogenetic Studies 2
- Cell Biology top 10%
- Spectroscopy top 5%
- Advanced Proteomics Techniques and Applications 4
- Genetics top 10%
- Glioma Diagnosis and Treatment 3
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- Cancer Mechanisms and Therapy 3
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- Neurofibromatosis and Schwannoma Cases 3
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- Cancer, Stress, Anesthesia, and Immune Response 2
- Co-authors
- Norie ArakiShujiro OkudaShin KawanoAkiyasu C. YoshizawaNaoyuki SugiyamaYu WatanabeYuki MoriyaSusumu Goto
- Journals
- Nucleic Acids Research (3 papers)Journal of Biological Chemistry (4 papers)Journal of Clinical Investigation (1 paper)
- Partner nations
- JapanUnited StatesThailand
In The Last Decade
Daiki Kobayashi
34 papers receiving 1.3k citations
Hit Papers
Peers
Comparison fields: 5 of 110
- Molecular Biology 820
- Cell Biology 184
- Spectroscopy 160
- Genetics 89
- Cancer Research 121
Countries citing papers authored by Daiki Kobayashi
This map shows the geographic impact of Daiki 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 Daiki Kobayashi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daiki Kobayashi more than expected).
Fields of papers citing papers by Daiki Kobayashi
This network shows the impact of papers produced by Daiki 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 Daiki Kobayashi. The network helps show where Daiki Kobayashi may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Daiki 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 | 2025 | 0 | |
| 2 | 2024 | 15 | |
| 3 | 2024 | 0 | |
| 4 | 2024 | 1 | |
| 5 | 2023 | 4 | |
| 6 | 2023 | 3 | |
| 7 | 2022 | 3 | |
| 8 | 2021 | 9 | |
| 9 | 2020 | 34 | |
| 10 | 2020 | 7 | |
| 11 | 2020 | 72 | |
| 12 | 2019 | 91 | |
| 13 | 2018 | 17 | |
| 14 | 2018 | 23 | |
| 15 | 2018 | 58 | |
| 16 | 2018 | 6 | |
| 17 | jPOSTrepo: an international standard data repository for proteomesbreakdown → | 2016 | 479 |
| 18 | 2015 | 5 | |
| 19 | 2013 | 20 | |
| 20 | 2003 | 15 |
About Daiki Kobayashi
Daiki Kobayashi is a scholar working on Metals and Alloys, Cell Biology and Molecular Biology, having authored 37 papers that have together received 1.3k indexed citations. Recurring topics across this work include Advanced Proteomics Techniques and Applications (4 papers), Metabolomics and Mass Spectrometry Studies (3 papers), Glioma Diagnosis and Treatment (3 papers), Ubiquitin and proteasome pathways (3 papers), Cancer Mechanisms and Therapy (3 papers), Neurofibromatosis and Schwannoma Cases (3 papers), Cancer, Stress, Anesthesia, and Immune Response (2 papers) and Genomics and Phylogenetic Studies (2 papers). The work is most often cited by research in Molecular Biology (820 citations), Cell Biology (184 citations) and Spectroscopy (160 citations). Daiki Kobayashi has collaborated with scholars based in Japan, United States and Thailand. Frequent co-authors include Norie Araki, Shujiro Okuda, Shin Kawano, Akiyasu C. Yoshizawa, Naoyuki Sugiyama, Yu Watanabe, Yuki Moriya, Susumu Goto, Yasushi Ishihama and Masaki Matsumoto. Their work appears in journals such as Nucleic Acids Research, Journal of Biological Chemistry and Journal of Clinical Investigation.
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.