Xin Ku
Impact in
- Toxicology top 5%
- Bioactive Compounds and Antitumor Agents
- Organic Chemistry top 10%
- Synthesis and biological activity
- Sulfur-Based Synthesis Techniques
- Chemical Synthesis and Reactions
- Synthesis and Characterization of Heterocyclic Compounds
Papers in
-
- Glycosylation and Glycoproteins Research 2
- Ubiquitin and proteasome pathways 2
- S100 Proteins and Annexins 2
- Oncology 4
- HER2/EGFR in Cancer Research 2
- Co-authors
- Hualiang Jiang (2 shared papers)Honglin Li (2 shared papers)Hong Liu (2 shared papers)He Huang (2 shared papers)Daqi Gao (1 shared paper)Jiayu Gong (1 shared paper)Wei Yan (14 shared papers)Ming Li (1 shared paper)
In The Last Decade
Xin Ku
24 papers receiving 748 citations
Peers
Comparison fields: 5 of 84
- Toxicology 46
- Organic Chemistry 266
- Computational Theory and Mathematics 128
- Molecular Biology 396
- Oncology 141
Countries citing papers authored by Xin Ku
This map shows the geographic impact of Xin Ku'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 Xin Ku with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xin Ku more than expected).
Fields of papers citing papers by Xin Ku
This network shows the impact of papers produced by Xin Ku. 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 Xin Ku. The network helps show where Xin Ku may publish in the future.
Co-authors
The 25 scholars most cited alongside Xin Ku, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 25 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2013 | 181 | |
| 2 | 2010 | 180 | |
| 3 | 2015 | 89 | |
| 4 | 2009 | 70 | |
| 5 | 2013 | 57 | |
| 6 | 2018 | 32 | |
| 7 | 2014 | 19 | |
| 8 | 2021 | 16 | |
| 9 | 2022 | 14 | |
| 10 | 2022 | 12 | |
| 11 | 2013 | 11 | |
| 12 | 2020 | 11 | |
| 13 | 2019 | 10 | |
| 14 | 2020 | 9 | |
| 15 | 2020 | 9 | |
| 16 | 2019 | 8 | |
| 17 | 2023 | 6 | |
| 18 | 2020 | 4 | |
| 19 | 2018 | 4 | |
| 20 | 2024 | 3 |
About Xin Ku
Xin Ku is a scholar working on Molecular Biology, Oncology, Neurology, Spectroscopy and Organic Chemistry, having authored 25 papers that have together received 754 indexed citations. Recurring topics across this work include Advanced Proteomics Techniques and Applications (3 papers), Myasthenia Gravis and Thymoma (3 papers), Glycosylation and Glycoproteins Research (2 papers), Ubiquitin and proteasome pathways (2 papers), S100 Proteins and Annexins (2 papers), Computational Drug Discovery Methods (2 papers), HER2/EGFR in Cancer Research (2 papers) and Lymphoma Diagnosis and Treatment (2 papers). The work is most often cited by research in Toxicology (46 citations), Organic Chemistry (266 citations), Computational Theory and Mathematics (128 citations), Molecular Biology (396 citations) and Oncology (141 citations). Xin Ku has collaborated with scholars based in China, Germany and Japan. Frequent co-authors include Hualiang Jiang, Honglin Li, Hong Liu, He Huang, Daqi Gao, Jiayu Gong, Wei Yan, Ming Li, Xiang Wang and Jian Ding. Their work appears in journals such as Journal of Proteome Research, Journal of Medicinal Chemistry, Biochimica et Biophysica Acta (BBA) - General Subjects, Bioinformatics and Biochemical and Biophysical Research Communications.
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.