Xiaojun Ding
Impact in
- Physiology top 1%
- Calcium signaling and nucleotide metabolism
- Epidemiology top 1%
- Autophagy in Disease and Therapy
Papers in
-
- Machine Learning in Bioinformatics 5
- Genomics and Chromatin Dynamics 5
- Epigenetics and DNA Methylation 4
- RNA and protein synthesis mechanisms 4
- Genetics 10
- Co-authors
- She Chen (15 shared papers)Du Lam (1 shared paper)Xuejun Jiang (1 shared paper)Junru Wang (1 shared paper)Ian G. Ganley (1 shared paper)Qing Zhong (4 shared papers)Weiliang Fan (4 shared papers)Qiming Sun (2 shared papers)
- Journals
- Journal of Biological Chemistry (4 papers)Textile Research Journal (3 papers)Nature (3 papers)Bioinformatics (2 papers)Tsinghua Science & Technology (2 papers)
- Partner nations
- ChinaUnited StatesCanada
In The Last Decade
Xiaojun Ding
57 papers receiving 3.8k citations
Xiaojun Ding's Hit Papers
Peers
Comparison fields: 5 of 143
- Physiology 316
- Epidemiology 1.8k
- Endocrinology 265
- Cell Biology 597
- Geriatrics and Gerontology 95
Countries citing papers authored by Xiaojun Ding
This map shows the geographic impact of Xiaojun Ding'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 Xiaojun Ding with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiaojun Ding more than expected).
Fields of papers citing papers by Xiaojun Ding
This network shows the impact of papers produced by Xiaojun Ding. 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 Xiaojun Ding. The network helps show where Xiaojun Ding may publish in the future.
Co-authors
The 25 scholars most cited alongside Xiaojun Ding, 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 63 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | ULK1·ATG13·FIP200 Complex Mediates mTOR Signaling and Is Essential for Autophagy Hit paper breakdown → | 2009 | 1265 |
| 2 | 2008 | 420 | |
| 3 | 2013 | 228 | |
| 4 | 2010 | 212 | |
| 5 | 2018 | 182 | |
| 6 | 2012 | 176 | |
| 7 | 2011 | 171 | |
| 8 | 2010 | 166 | |
| 9 | 2010 | 119 | |
| 10 | 2014 | 106 | |
| 11 | 2016 | 99 | |
| 12 | 2009 | 88 | |
| 13 | 2018 | 80 | |
| 14 | 2011 | 78 | |
| 15 | 2018 | 68 | |
| 16 | 2013 | 59 | |
| 17 | 2012 | 54 | |
| 18 | 2010 | 29 | |
| 19 | 2014 | 26 | |
| 20 | 2012 | 24 |
About Xiaojun Ding
Xiaojun Ding is a scholar working on Molecular Biology, Genetics, Artificial Intelligence, Neurology and Cognitive Neuroscience, having authored 63 papers that have together received 3.9k indexed citations. Recurring topics across this work include Autophagy in Disease and Therapy (6 papers), Myasthenia Gravis and Thymoma (5 papers), Machine Learning in Bioinformatics (5 papers), Endoplasmic Reticulum Stress and Disease (5 papers), Genomics and Chromatin Dynamics (5 papers), Epigenetics and DNA Methylation (4 papers), RNA and protein synthesis mechanisms (4 papers) and Neural dynamics and brain function (4 papers). The work is most often cited by research in Physiology (316 citations), Epidemiology (1.8k citations), Endocrinology (265 citations), Cell Biology (597 citations) and Geriatrics and Gerontology (95 citations). Xiaojun Ding has collaborated with scholars based in China, United States and Canada. Frequent co-authors include She Chen, Du Lam, Xuejun Jiang, Junru Wang, Ian G. Ganley, Qing Zhong, Weiliang Fan, Qiming Sun, Keling Chen and Feng Shao. Their work appears in journals such as Journal of Biological Chemistry, Textile Research Journal, Nature, Bioinformatics and Tsinghua Science & Technology.
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.