Hong Cheng

1.7k total citations
36 papers, 1.0k citations indexed

About

Hong Cheng is a scholar working on Genetics, Public Health, Environmental and Occupational Health and Molecular Biology. According to data from OpenAlex, Hong Cheng has authored 36 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Genetics, 8 papers in Public Health, Environmental and Occupational Health and 7 papers in Molecular Biology. Recurrent topics in Hong Cheng's work include Genetic Associations and Epidemiology (23 papers), Nutrition, Genetics, and Disease (10 papers) and Obesity, Physical Activity, Diet (8 papers). Hong Cheng is often cited by papers focused on Genetic Associations and Epidemiology (23 papers), Nutrition, Genetics, and Disease (10 papers) and Obesity, Physical Activity, Diet (8 papers). Hong Cheng collaborates with scholars based in China, United States and Samoa. Hong Cheng's co-authors include Jie Mi, Dongqing Hou, Xiaoyuan Zhao, Bo Xi, Yue Shen, Lijun Wu, Guangyun Sun, Ranjan Deka, Daniel E. Weeks and Stephen T. McGarvey and has published in prestigious journals such as Nature Genetics, PLoS ONE and The Journal of Clinical Endocrinology & Metabolism.

In The Last Decade

Hong Cheng

34 papers receiving 1.0k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Hong Cheng China 17 420 305 251 193 155 36 1.0k
Marina T. DiStefano United States 13 567 1.4× 500 1.6× 152 0.6× 243 1.3× 121 0.8× 27 1.4k
Heather Mason‐Suares United States 14 454 1.1× 370 1.2× 157 0.6× 116 0.6× 92 0.6× 25 981
Elisabeth Widén Finland 13 321 0.8× 351 1.2× 96 0.4× 434 2.2× 55 0.4× 28 1.2k
Patrizia Pasanisi Italy 21 241 0.6× 633 2.1× 176 0.7× 237 1.2× 339 2.2× 59 1.4k
Josef Včelák Czechia 22 270 0.6× 295 1.0× 108 0.4× 207 1.1× 65 0.4× 81 1.3k
Tiina Jääskeläinen Finland 23 281 0.7× 846 2.8× 103 0.4× 106 0.5× 166 1.1× 68 1.7k
Bilgin Gürateş United States 28 997 2.4× 356 1.2× 408 1.6× 107 0.6× 127 0.8× 51 2.9k
Isabel Sousa Portugal 7 396 0.9× 540 1.8× 76 0.3× 236 1.2× 110 0.7× 8 1.0k
Kerry J. McInnes United Kingdom 18 246 0.6× 285 0.9× 85 0.3× 173 0.9× 66 0.4× 22 953
Jannel Liu United States 3 496 1.2× 574 1.9× 69 0.3× 201 1.0× 98 0.6× 5 995

Countries citing papers authored by Hong Cheng

Since Specialization
Citations

This map shows the geographic impact of Hong 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 Hong Cheng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hong Cheng more than expected).

Fields of papers citing papers by Hong Cheng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hong 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 Hong Cheng. The network helps show where Hong Cheng may publish in the future.

Co-authorship network of co-authors of Hong Cheng

This figure shows the co-authorship network connecting the top 25 collaborators of Hong Cheng. A scholar is included among the top collaborators of Hong Cheng based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Hong Cheng. Hong Cheng is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Li, Wanqian, Yan Zou, Jiaojiao Zhang, et al.. (2025). Transcription factor EGR2 drives cataract formation through IGFBP3-mediated oxidative injury in lens epithelial cells. Free Radical Biology and Medicine. 241. 773–788.
2.
Wang, Shengyong, et al.. (2024). Using Network Analysis to Subgroup Risk Factors for Depressive Symptoms in College Students. Psychology Research and Behavior Management. Volume 17. 3625–3636.
3.
Russell, Emily M., Jenna C. Carlson, Nicola L. Hawley, et al.. (2022). CREBRF missense variant rs373863828 has both direct and indirect effects on type 2 diabetes and fasting glucose in Polynesian peoples living in Samoa and Aotearoa New Zealand. BMJ Open Diabetes Research & Care. 10(1). e002275–e002275. 4 indexed citations
4.
Hawley, Nicola L., Jenna C. Carlson, Emily M. Russell, et al.. (2022). The missense variant, rs373863828, in CREBRF plays a role in longitudinal changes in body mass index in Samoans. Obesity Research & Clinical Practice. 16(3). 220–227. 3 indexed citations
5.
Fu, Liwan, et al.. (2022). Distinct causal effects of body fat distribution on cardiometabolic traits among children: Findings from the BCAMS study. Nutrition Metabolism and Cardiovascular Diseases. 32(7). 1753–1765. 12 indexed citations
6.
7.
8.
Li, Lujiao, Jinhua Yin, Hong Cheng, et al.. (2016). Identification of Genetic and Environmental Factors Predicting Metabolically Healthy Obesity in Children: Data From the BCAMS Study. The Journal of Clinical Endocrinology & Metabolism. 101(4). 1816–1825. 63 indexed citations
9.
Wu, Lijun, Xiaoyuan Zhao, Yue Shen, et al.. (2015). Influence of lifestyle on the FAIM2 promoter methylation between obese and lean children: a cohort study. BMJ Open. 5(4). e007670–e007670. 13 indexed citations
10.
Zhang, Meixian, Xiaoyuan Zhao, Bo Xi, et al.. (2014). [Impact of obesity-related gene polymorphism on risk of obesity and metabolic disorder in childhood].. PubMed. 48(9). 776–83. 5 indexed citations
11.
Xi, Bo, Xiaoyuan Zhao, Yue Shen, et al.. (2014). An obesity genetic risk score predicts risk of insulin resistance among Chinese children. Endocrine. 47(3). 825–832. 12 indexed citations
12.
Wang, Anlai, Rita Greco, Zhifang Li, et al.. (2014). Combination of PIM and JAK2 inhibitors synergistically suppresses cell proliferation and overcomes drug resistance of myeloproliferative neoplasms. Oncotarget. 5(10). 3362–3374. 24 indexed citations
13.
Zhao, Xiaoyuan, Meixian Zhang, Hong Cheng, et al.. (2013). [Risk of obesity-related gene polymorphism on the incidence and durative of childhood obesity].. PubMed. 34(6). 560–5. 5 indexed citations
14.
Zhao, Xiaoyuan, Bo Xi, Yue Shen, et al.. (2013). An obesity genetic risk score is associated with metabolic syndrome in Chinese children. Gene. 535(2). 299–302. 33 indexed citations
15.
Xi, Bo, Xiaoyuan Zhao, Yue Shen, et al.. (2013). Associations of obesity susceptibility loci with hypertension in Chinese children. International Journal of Obesity. 37(7). 926–930. 20 indexed citations
16.
Zhang, Ge, Rebekah Karns, Guangyun Sun, et al.. (2012). Finding Missing Heritability in Less Significant Loci and Allelic Heterogeneity: Genetic Variation in Human Height. PLoS ONE. 7(12). e51211–e51211. 18 indexed citations
17.
Cheng, Hong, Yinkun Yan, & Jie Mi. (2011). T-001 ASSOCIATION BETWEEN OBESITY IN CHILDHOOD AND HYPERTENSION INCIDENCE. Journal of Hypertension. 29. e51–e51. 1 indexed citations
18.
Meng, Linghui, Na Luo, Hong Cheng, et al.. (2011). [Waist circumference reference values in Beijing versus the national values in detecting cardiovascular risk factors in 7-18 years old children].. PubMed. 45(8). 717–22. 2 indexed citations
19.
Xi, Bo, Yue Shen, Meixian Zhang, et al.. (2010). The common rs9939609 variant of the fat mass and obesity-associated gene is associated with obesity risk in children and adolescents of Beijing, China. BMC Medical Genetics. 11(1). 107–107. 92 indexed citations
20.
Zhang, Ge, Rebekah Karns, Nina Smolej Narančić, et al.. (2010). Common SNPs in FTO Gene Are Associated with Obesity Related Anthropometric Traits in an Island Population from the Eastern Adriatic Coast of Croatia. PLoS ONE. 5(4). e10375–e10375. 30 indexed citations

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.

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