Chang Jun
Impact in
- Physiology top 1%
- Calcium signaling and nucleotide metabolism
- Epidemiology top 2%
- Autophagy in Disease and Therapy
Papers in
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- Calcium signaling and nucleotide metabolism 1
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- Blockchain Technology Applications and Security 1
- Co-authors
- Do‐Hyung Kim (1 shared paper)Young Mi Kim (1 shared paper)Chang Hwa Jung (1 shared paper)Neil Otto (1 shared paper)Seung‐Hyun Ro (1 shared paper)Jing Cao (1 shared paper)Mondira Kundu (1 shared paper)Feng Tang (1 shared paper)
- Journals
- Molecular Biology of the Cell (1 paper)Chinese Journal of Computers (1 paper)Zhongcaoyao (1 paper)DOAJ (DOAJ: Directory of Open Access Journals) (1 paper)
- Partner nations
- ChinaUnited StatesTaiwan
In The Last Decade
Chang Jun
6 papers receiving 1.7k citations
Chang Jun's Hit Papers
Peers
Comparison fields: 5 of 100
- Physiology 218
- Epidemiology 1.2k
- Geriatrics and Gerontology 93
- Cell Biology 334
- Aging 31
Countries citing papers authored by Chang Jun
This map shows the geographic impact of Chang Jun'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 Chang Jun with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chang Jun more than expected).
Fields of papers citing papers by Chang Jun
This network shows the impact of papers produced by Chang Jun. 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 Chang Jun. The network helps show where Chang Jun may publish in the future.
Co-authors
The 12 scholars most cited alongside Chang Jun, 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 | ULK-Atg13-FIP200 Complexes Mediate mTOR Signaling to the Autophagy Machinery Hit paper breakdown → | 2009 | 1684 |
| 2 | DyTrust: A Time-Frame Based Dynamic Trust Model for P2P Systems | 2006 | 21 |
| 3 | On the Model Tests for POD Propulsion Ships | 2005 | 4 |
| 4 | Identification of Trapa L. plant along middle-low reaches of Changjiang River by analyzing their DNA sequences | 2004 | 4 |
| 5 | 2011 | 1 | |
| 6 | Determination of 6,7-Dehydroroyleanone in Salvia Deserta Schang by UV | 2001 | 1 |
| 7 | 2018 | 0 |
About Chang Jun
Chang Jun is a scholar working on Physiology, Information Systems, Hardware and Architecture, Complementary and alternative medicine and Environmental Engineering, having authored 7 papers that have together received 1.7k indexed citations. Recurring topics across this work include Distributed and Parallel Computing Systems (1 paper), Forest, Soil, and Plant Ecology in China (1 paper), Blockchain Technology Applications and Security (1 paper), Engineering Applied Research (1 paper), Marine and Coastal Research (1 paper), Parallel Computing and Optimization Techniques (1 paper), Remote Sensing and Land Use (1 paper) and Calcium signaling and nucleotide metabolism (1 paper). The work is most often cited by research in Physiology (218 citations), Epidemiology (1.2k citations), Geriatrics and Gerontology (93 citations), Cell Biology (334 citations) and Aging (31 citations). Chang Jun has collaborated with scholars based in China, United States and Taiwan. Frequent co-authors include Do‐Hyung Kim, Young Mi Kim, Chang Hwa Jung, Neil Otto, Seung‐Hyun Ro, Jing Cao, Mondira Kundu, Feng Tang, Jie Shen and Ping Chen. Their work appears in journals such as Molecular Biology of the Cell, Chinese Journal of Computers, Zhongcaoyao and DOAJ (DOAJ: Directory of Open Access Journals).
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.