Keding Cheng
Impact in
- Virology top 5%
- HIV Research and Treatment
- Clinical Biochemistry top 5%
- Bacterial Identification and Susceptibility Testing
Papers in
-
- Viral Infections and Outbreaks Research 4
- Viral Infections and Vectors 3
-
- Cell death mechanisms and regulation 4
- Co-authors
- Satya Saxena (4 shared papers)Surender Kharbanda (4 shared papers)Pramod S. Pandey (3 shared papers)Donald Küfe (3 shared papers)John A. Wilkins (7 shared papers)Pradip K. Majumder (2 shared papers)Gehua Wang (10 shared papers)Rakesh Datta (1 shared paper)
- Journals
- Journal of Clinical Microbiology (4 papers)Journal of Biological Chemistry (4 papers)PLoS ONE (3 papers)Journal of Proteomics (2 papers)PROTEOMICS - CLINICAL APPLICATIONS (2 papers)
- Partner nations
- CanadaChinaUnited States
In The Last Decade
Keding Cheng
39 papers receiving 1.5k citations
Peers
Comparison fields: 5 of 105
- Virology 80
- Clinical Biochemistry 103
- Infectious Diseases 237
- Molecular Biology 823
- Endocrinology 43
Countries citing papers authored by Keding Cheng
This map shows the geographic impact of Keding Cheng'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 Keding Cheng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Keding Cheng more than expected).
Fields of papers citing papers by Keding Cheng
This network shows the impact of papers produced by Keding Cheng. 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 Keding Cheng. The network helps show where Keding Cheng may publish in the future.
Co-authors
The 25 scholars most cited alongside Keding Cheng, 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 39 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2000 | 386 | |
| 2 | 2000 | 273 | |
| 3 | 2003 | 144 | |
| 4 | 2004 | 132 | |
| 5 | 2016 | 91 | |
| 6 | 2008 | 69 | |
| 7 | 2013 | 39 | |
| 8 | 1987 | 36 | |
| 9 | 2015 | 35 | |
| 10 | 2017 | 33 | |
| 11 | 2018 | 32 | |
| 12 | 2003 | 25 | |
| 13 | 1999 | 23 | |
| 14 | 2002 | 22 | |
| 15 | 2016 | 18 | |
| 16 | 2005 | 18 | |
| 17 | 2014 | 18 | |
| 18 | 2004 | 15 | |
| 19 | 2014 | 14 | |
| 20 | 2006 | 14 |
About Keding Cheng
Keding Cheng is a scholar working on Infectious Diseases, Molecular Biology, Epidemiology, Clinical Biochemistry and Endocrinology, having authored 39 papers that have together received 1.5k indexed citations. Recurring topics across this work include Bacterial Identification and Susceptibility Testing (6 papers), Cell death mechanisms and regulation (4 papers), Infective Endocarditis Diagnosis and Management (4 papers), Viral Infections and Outbreaks Research (4 papers), Escherichia coli research studies (4 papers), Advanced Proteomics Techniques and Applications (3 papers), Hepatitis B Virus Studies (3 papers) and Viral Infections and Vectors (3 papers). The work is most often cited by research in Virology (80 citations), Clinical Biochemistry (103 citations), Infectious Diseases (237 citations), Molecular Biology (823 citations) and Endocrinology (43 citations). Keding Cheng has collaborated with scholars based in Canada, China and United States. Frequent co-authors include Satya Saxena, Surender Kharbanda, Pramod S. Pandey, Donald Küfe, John A. Wilkins, Pradip K. Majumder, Gehua Wang, Rakesh Datta, Xiangao Sun and Angela Campbell. Their work appears in journals such as Journal of Clinical Microbiology, Journal of Biological Chemistry, PLoS ONE, Journal of Proteomics and PROTEOMICS - CLINICAL APPLICATIONS.
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.