Hua Yao

2.5k total citations · 1 hit paper
106 papers, 1.9k citations indexed

About

Hua Yao is a scholar working on Molecular Biology, Cardiology and Cardiovascular Medicine and Endocrinology, Diabetes and Metabolism. According to data from OpenAlex, Hua Yao has authored 106 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Molecular Biology, 22 papers in Cardiology and Cardiovascular Medicine and 21 papers in Endocrinology, Diabetes and Metabolism. Recurrent topics in Hua Yao's work include Liver Disease Diagnosis and Treatment (16 papers), Gout, Hyperuricemia, Uric Acid (12 papers) and Diabetes, Cardiovascular Risks, and Lipoproteins (11 papers). Hua Yao is often cited by papers focused on Liver Disease Diagnosis and Treatment (16 papers), Gout, Hyperuricemia, Uric Acid (12 papers) and Diabetes, Cardiovascular Risks, and Lipoproteins (11 papers). Hua Yao collaborates with scholars based in China, United States and Australia. Hua Yao's co-authors include Zhuo Zhang, Dong‐Ya Zhu, Chun‐Xia Luo, Xiao Han, Xianglin Shi, Qi‐Gang Zhou, Mei Hu, Weizheng Xu, Yao Hu and Bin Wang and has published in prestigious journals such as PLoS ONE, Scientific Reports and Chemosphere.

In The Last Decade

Hua Yao

101 papers receiving 1.9k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Resistance reduction method for building transmission and distribution systems based on an improved random forest model: A tee case study

2025 33 citations Wanqing Zhang, Hua Yao et al. Building and Environment profile →

Peers

Hua Yao

MB

EPIDE

PHYSI

EDM

NEURO

Ke Wang China

Xiaoming Zhong China

Şule Çetınel Türkiye

Yu Yan China

Guanjie Chen United States

Gholamreza Hassanzadeh Iran

Ali Noorafshan Iran

Wei Yan China

Muhammad Imran Khan Pakistan

Ke Wang China

Hua Yao

432 ×1.0

MB

175 ×0.7

EPIDE

292 ×1.2

PHYSI

218 ×1.0

EDM

144 ×0.8

NEURO

Citations per year, relative to Hua Yao Hua Yao (= 1×) peers Ke Wang

Countries citing papers authored by Hua Yao

Since Specialization

Citations

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

Fields of papers citing papers by Hua Yao

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hua Yao

This figure shows the co-authorship network connecting the top 25 collaborators of Hua Yao. A scholar is included among the top collaborators of Hua Yao 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 Hua Yao. Hua Yao is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

1.

Hu, Xiaoyuan, et al.. (2025). Association Between ABCG1/TCF7L2 and Type 2 Diabetes Mellitus: An Intervention Trial Based on a Case–Control Study. Journal of Diabetes Research. 2025(1). 9356676–9356676. 1 indexed citations

2.

Zhang, Wanqing, et al.. (2025). Resistance reduction method for building transmission and distribution systems based on an improved random forest model: A tee case study. Building and Environment. 282. 113256–113256. 33 indexed citations breakdown →

3.

Ji, Weidong, Yushan Wang, Xiaoxuan Liu, et al.. (2023). Exposure to ambient air pollution and chronic bronchitis: Findings from over 6.6 million adults in northwestern China. Chemosphere. 350. 140993–140993. 3 indexed citations

4.

Liu, Te, Yang Li, Jun Zhang, et al.. (2023). Effects of magnetically targeted iron oxide@polydopamine-labeled human umbilical cord mesenchymal stem cells in cerebral infarction in mice. Aging. 15(4). 1130–1142. 7 indexed citations

5.

Meng, Kun, Xiao‐Ming Chen, Hua Yao, et al.. (2021). Preparation, Characterization, and In Vivo Evaluation of Amorphous Icaritin Nanoparticles Prepared by a Reactive Precipitation Technique. Molecules. 26(10). 2913–2913. 10 indexed citations

6.

Lu, Yaoqin, Wenli Li, Chen Chen, et al.. (2020). <p>Prevalence and Correlation of Metabolic Syndrome: A Cross-Sectional Study of Nearly 10 Million Multi-Ethnic Chinese Adults</p>. Diabetes Metabolic Syndrome and Obesity. Volume 13. 4869–4883. 5 indexed citations

7.

Li, Xiuying, Liya Wu, Huiying Lv, et al.. (2020). Efficacy of Fe₃O₄@polydopamine nanoparticle-labeled human umbilical cord Wharton's jelly-derived mesenchymal stem cells in the treatment of streptozotocin-induced diabetes in rats. Biomaterials Science. 8(19). 5362–5375. 18 indexed citations

8.

Mao, Jiangfeng, Xiaoyun Zeng, Quan Li, et al.. (2018). The Constellation of Macrovascular Risk Factors in Early Onset T2DM: A Cross-Sectional Study in Xinjiang Province, China. Journal of Diabetes Research. 2018. 1–8. 3 indexed citations

9.

Yao, Hua, et al.. (2017). Enteral versus parenteral nutrition in critically ill patients with severe pancreatitis: a meta-analysis. European Journal of Clinical Nutrition. 72(1). 66–68. 36 indexed citations

10.

Liu, Jianbo, et al.. (2016). [Study on the relationship between dietary patterns and metabolic syndrome and its components in Xinjiang Uygur population].. PubMed. 45(5). 725–732. 3 indexed citations

11.

Sun, Yuping, Rong Wei, Dandan Yan, et al.. (2016). Association between APOE polymorphism and metabolic syndrome in Uyghur ethnic men. BMJ Open. 6(1). e010049–e010049. 15 indexed citations

12.

Wang, Zhiqiang, Hua Yao, Tingting Wang, et al.. (2015). [Association between type 2 diabetes in Uygur and polymorphisms of SLC30A8 and its interaction with smoking].. PubMed. 36(10). 1167–71. 1 indexed citations

13.

Miao, Lei, et al.. (2015). A meta-analysis of the associations between the Q141K and Q126X ABCG2 gene variants and gout risk.. PubMed Central. 8(9). 9812–23. 25 indexed citations

14.

Liu, Yongbing, et al.. (2013). The status quo and influencing factors of health literacy in nursing homes of Urumuqi. 7(2). 117–120. 1 indexed citations

15.

Liu, Yongbing, et al.. (2013). Health literacy and social support in nursing homes. 7(5). 308–311. 1 indexed citations

16.

Yao, Hua. (2012). Study of Differentially Expressed Serun Proteins in Primary Hyperuricemia in Uyghur by 2-DE and MALDI-TOF-MS. Biotechnology(Faisalabad). 2 indexed citations

17.

Cai, Wen, et al.. (2012). The associaion of serum uric acid level with prevalence of non-alcoholic fatty liver in Uyghur and Han ethnicities. Zhonghua neifenmi daixie zazhi. 28(11). 890–894. 1 indexed citations

18.

Yao, Hua, Weizheng Xu, Xianglin Shi, & Zhuo Zhang. (2011). Dietary Flavonoids as Cancer Prevention Agents. Journal of Environmental Science and Health Part A Environmental Science and Engineering and Toxicology. 2 indexed citations

19.

Yao, Hua. (2007). The analysis of uric acid level and the prevalence of hyperuricmia in Uygur ethnic population. Xinjiang Yike Daxue xuebao. 2 indexed citations

20.

Yao, Hua. (2005). Excess fluoride and metabolic changes of cartilage. 1 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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