Xiaoling Wang
Impact in
- Aging top 2%
- Behavioral Neuroscience top 2%
Papers in
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- Epigenetics and DNA Methylation 20
-
- Heart Rate Variability and Autonomic Control 14
- Blood Pressure and Hypertension Studies 11
- Co-authors
- Harold Snieder (51 shared papers)Shaoyong Su (53 shared papers)Frank A. Treiber (35 shared papers)Gregory A. Harshfield (22 shared papers)Daniel Yuan (5 shared papers)Xuewen Pan (5 shared papers)Jef D. Boeke (5 shared papers)Joel S. Bader (3 shared papers)
- Journals
- Twin Research and Human Genetics (6 papers)Scientific Reports (5 papers)Hypertension (5 papers)Journal of Hypertension (5 papers)Circulation (4 papers)
- Partner nations
- United StatesNetherlandsUnited Kingdom
In The Last Decade
Xiaoling Wang
126 papers receiving 5.0k citations
Peers
Comparison fields: 5 of 154
- Aging 90
- Behavioral Neuroscience 167
- Cardiology and Cardiovascular Medicine 815
- Business and International Management 70
- Molecular Biology 2.1k
Countries citing papers authored by Xiaoling Wang
This map shows the geographic impact of Xiaoling Wang'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 Xiaoling Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiaoling Wang more than expected).
Fields of papers citing papers by Xiaoling Wang
This network shows the impact of papers produced by Xiaoling Wang. 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 Xiaoling Wang. The network helps show where Xiaoling Wang may publish in the future.
Co-authors
The 25 scholars most cited alongside Xiaoling Wang, 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 134 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2006 | 441 | |
| 2 | 2015 | 351 | |
| 3 | 2004 | 255 | |
| 4 | 2011 | 224 | |
| 5 | 2007 | 179 | |
| 6 | 2015 | 161 | |
| 7 | 2006 | 154 | |
| 8 | 2015 | 150 | |
| 9 | 2013 | 142 | |
| 10 | 2015 | 137 | |
| 11 | 2009 | 136 | |
| 12 | 2010 | 127 | |
| 13 | 2014 | 114 | |
| 14 | 2017 | 108 | |
| 15 | 2003 | 90 | |
| 16 | 2012 | 89 | |
| 17 | 2005 | 83 | |
| 18 | 2014 | 75 | |
| 19 | 2016 | 72 | |
| 20 | 2008 | 68 |
About Xiaoling Wang
Xiaoling Wang is a scholar working on Molecular Biology, Cardiology and Cardiovascular Medicine, Genetics, Physiology and Pediatrics, Perinatology and Child Health, having authored 134 papers that have together received 5.1k indexed citations. Recurring topics across this work include Epigenetics and DNA Methylation (20 papers), Heart Rate Variability and Autonomic Control (14 papers), Blood Pressure and Hypertension Studies (11 papers), Birth, Development, and Health (10 papers), Genetic Associations and Epidemiology (9 papers), Stress Responses and Cortisol (9 papers), Hormonal Regulation and Hypertension (9 papers) and Adipose Tissue and Metabolism (6 papers). The work is most often cited by research in Aging (90 citations), Behavioral Neuroscience (167 citations), Cardiology and Cardiovascular Medicine (815 citations), Business and International Management (70 citations) and Molecular Biology (2.1k citations). Xiaoling Wang has collaborated with scholars based in United States, Netherlands and United Kingdom. Frequent co-authors include Harold Snieder, Shaoyong Su, Frank A. Treiber, Gregory A. Harshfield, Daniel Yuan, Xuewen Pan, Jef D. Boeke, Joel S. Bader, Haidong Zhu and Yanbin Dong. Their work appears in journals such as Twin Research and Human Genetics, Scientific Reports, Hypertension, Journal of Hypertension and Circulation.
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.