Sha Guan
Impact in
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- Renin-Angiotensin System Studies
- Blood Pressure and Hypertension Studies
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- Hormonal Regulation and Hypertension
Papers in
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- Protein Interaction Studies and Fluorescence Analysis 1
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- Blood properties and coagulation 1
- Pulmonary Hypertension Research and Treatments 1
- Co-authors
- John Fox (2 shared papers)L. Gabriel Navar (2 shared papers)Kenneth D. Mitchell (1 shared paper)Anka Hymel (1 shared paper)Vecihi Batuman (2 shared papers)Steffen‐Sebastian Bolz (1 shared paper)Changsen Wang (1 shared paper)Roman Zyla (1 shared paper)
- Journals
- American Journal of Physiology-Renal Physiology (2 papers)Hypertension (1 paper)Molecular Biology of the Cell (1 paper)Molecular Immunology (1 paper)PubMed (1 paper)
- Partner nations
- United StatesCanadaChina
In The Last Decade
Sha Guan
6 papers receiving 448 citations
Peers
Comparison fields: 5 of 57
- Cardiology and Cardiovascular Medicine 219
- Endocrinology, Diabetes and Metabolism 142
- Nephrology 39
- Genetics 33
- Biochemistry 24
Countries citing papers authored by Sha Guan
This map shows the geographic impact of Sha Guan'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 Sha Guan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sha Guan more than expected).
Fields of papers citing papers by Sha Guan
This network shows the impact of papers produced by Sha Guan. 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 Sha Guan. The network helps show where Sha Guan may publish in the future.
Co-authors
The 21 scholars most cited alongside Sha Guan, 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 | 1992 | 160 | |
| 2 | 1992 | 139 | |
| 3 | 2014 | 73 | |
| 4 | 1997 | 46 | |
| 5 | Inhibition of Na-K-ATPase activity and gene expression by a myeloma light chain in proximal tubule cells. | 1999 | 26 |
| 6 | 2011 | 9 |
About Sha Guan
Sha Guan is a scholar working on Molecular Biology, Pulmonary and Respiratory Medicine, Physiology, Cell Biology and Cardiology and Cardiovascular Medicine, having authored 6 papers that have together received 453 indexed citations. Recurring topics across this work include Erythrocyte Function and Pathophysiology (2 papers), Blood properties and coagulation (1 paper), Diet and metabolism studies (1 paper), Cytokine Signaling Pathways and Interactions (1 paper), Pulmonary Hypertension Research and Treatments (1 paper), Hemoglobin structure and function (1 paper), Renin-Angiotensin System Studies (1 paper) and Protein Interaction Studies and Fluorescence Analysis (1 paper). The work is most often cited by research in Cardiology and Cardiovascular Medicine (219 citations), Endocrinology, Diabetes and Metabolism (142 citations), Nephrology (39 citations), Genetics (33 citations) and Biochemistry (24 citations). Sha Guan has collaborated with scholars based in United States, Canada and China. Frequent co-authors include John Fox, L. Gabriel Navar, Kenneth D. Mitchell, Anka Hymel, Vecihi Batuman, Steffen‐Sebastian Bolz, Changsen Wang, Roman Zyla, Jun Liu and Bryan Heit. Their work appears in journals such as American Journal of Physiology-Renal Physiology, Hypertension, Molecular Biology of the Cell, Molecular Immunology and PubMed.
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.