Nan Bing
Impact in
- Pharmacology top 5%
- Pharmacogenetics and Drug Metabolism
- Drug-Induced Hepatotoxicity and Protection
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- Bioinformatics and Genomic Networks
- Gene Regulatory Network Analysis
- Gene expression and cancer classification
- Renal and related cancers
Papers in
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- Renal and related cancers 3
- Gene expression and cancer classification 3
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- Renal cell carcinoma treatment 5
- Co-authors
- Ina Hoeschele (3 shared papers)Alberto de la Fuente (1 shared paper)Pedro Mendes (1 shared paper)Colin F. Spraggs (8 shared papers)Vincent Mooser (7 shared papers)John C. Whittaker (5 shared papers)Lon R. Cardon (4 shared papers)Linda P. Briley (3 shared papers)
- Journals
- Journal of Clinical Oncology (6 papers)British Journal of Cancer (1 paper)Human Molecular Genetics (1 paper)Veterinary Immunology and Immunopathology (1 paper)PPAR Research (1 paper)
- Partner nations
- United StatesUnited KingdomJapan
In The Last Decade
Nan Bing
20 papers receiving 1.0k citations
Peers
Comparison fields: 5 of 122
- Pharmacology 131
- Molecular Biology 576
- Cancer Research 110
- Internal Medicine 25
- Hematology 66
Countries citing papers authored by Nan Bing
This map shows the geographic impact of Nan Bing'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 Nan Bing with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nan Bing more than expected).
Fields of papers citing papers by Nan Bing
This network shows the impact of papers produced by Nan Bing. 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 Nan Bing. The network helps show where Nan Bing may publish in the future.
Co-authors
The 25 scholars most cited alongside Nan Bing, 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 | 2004 | 392 | |
| 2 | 2011 | 199 | |
| 3 | 2011 | 111 | |
| 4 | 2005 | 74 | |
| 5 | 2016 | 73 | |
| 6 | 2011 | 35 | |
| 7 | 2019 | 33 | |
| 8 | 2015 | 28 | |
| 9 | 2018 | 27 | |
| 10 | 2021 | 16 | |
| 11 | 2013 | 14 | |
| 12 | 2011 | 11 | |
| 13 | 2021 | 7 | |
| 14 | 2010 | 6 | |
| 15 | 2009 | 5 | |
| 16 | 2011 | 5 | |
| 17 | 2005 | 3 | |
| 18 | 2016 | 2 | |
| 19 | 2009 | 1 | |
| 20 | 2010 | 1 |
About Nan Bing
Nan Bing is a scholar working on Molecular Biology, Pulmonary and Respiratory Medicine, Genetics, Cancer Research and Oncology, having authored 20 papers that have together received 1.0k indexed citations. Recurring topics across this work include Renal cell carcinoma treatment (5 papers), Chronic Lymphocytic Leukemia Research (3 papers), Renal and related cancers (3 papers), Cancer Genomics and Diagnostics (3 papers), Gene expression and cancer classification (3 papers), T-cell and B-cell Immunology (2 papers), Genetic Mapping and Diversity in Plants and Animals (2 papers) and Genetic Associations and Epidemiology (2 papers). The work is most often cited by research in Pharmacology (131 citations), Molecular Biology (576 citations), Cancer Research (110 citations), Internal Medicine (25 citations) and Hematology (66 citations). Nan Bing has collaborated with scholars based in United States, United Kingdom and Japan. Frequent co-authors include Ina Hoeschele, Alberto de la Fuente, Pedro Mendes, Colin F. Spraggs, Vincent Mooser, John C. Whittaker, Lon R. Cardon, Linda P. Briley, Charles Cox and Karen S. King. Their work appears in journals such as Journal of Clinical Oncology, British Journal of Cancer, Human Molecular Genetics, Veterinary Immunology and Immunopathology and PPAR Research.
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.