Yang Hai

4.0k total citations
31 papers, 447 citations indexed

About

Yang Hai is a scholar working on Molecular Biology, Ophthalmology and Genetics. According to data from OpenAlex, Yang Hai has authored 31 papers receiving a total of 447 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Molecular Biology, 6 papers in Ophthalmology and 6 papers in Genetics. Recurrent topics in Yang Hai's work include Genetic Associations and Epidemiology (4 papers), Alzheimer's disease research and treatments (4 papers) and Bioinformatics and Genomic Networks (3 papers). Yang Hai is often cited by papers focused on Genetic Associations and Epidemiology (4 papers), Alzheimer's disease research and treatments (4 papers) and Bioinformatics and Genomic Networks (3 papers). Yang Hai collaborates with scholars based in China, United States and New Zealand. Yang Hai's co-authors include Xiuqing Guo, Jerome I. Rotter, Bingshan Li, Qiang Wei, Mark O. Goodarzi, Xue Zhong, Ronald M. Krauss, Richard S. Legro, Ricardo Azziz and Michelle R. Jones and has published in prestigious journals such as Journal of the American Chemical Society, Nature Neuroscience and Bioinformatics.

In The Last Decade

Yang Hai

31 papers receiving 444 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Yang Hai China 12 190 86 61 57 55 31 447
Ge Gao China 15 154 0.8× 16 0.2× 50 0.8× 75 1.3× 87 1.6× 29 523
Yanhong Wang China 11 182 1.0× 81 0.9× 23 0.4× 10 0.2× 49 0.9× 36 500
Cristina Alvarez Spain 9 169 0.9× 65 0.8× 17 0.3× 113 2.0× 75 1.4× 16 401
M Okamoto Japan 14 137 0.7× 80 0.9× 12 0.2× 33 0.6× 65 1.2× 32 541
Zhanwen He China 10 206 1.1× 47 0.5× 12 0.2× 59 1.0× 41 0.7× 33 360
Kiriko Kaneko Japan 13 402 2.1× 30 0.3× 23 0.4× 33 0.6× 76 1.4× 20 624
Carmel McVicar United Kingdom 10 119 0.6× 21 0.2× 176 2.9× 9 0.2× 42 0.8× 13 505
Céline Bris France 13 355 1.9× 60 0.7× 10 0.2× 34 0.6× 90 1.6× 35 515
Jens Hudemann Germany 10 217 1.1× 84 1.0× 9 0.1× 88 1.5× 158 2.9× 13 524
Kinga Hadzsiev Hungary 14 316 1.7× 212 2.5× 8 0.1× 34 0.6× 82 1.5× 73 624

Countries citing papers authored by Yang Hai

Since Specialization
Citations

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

Fields of papers citing papers by Yang Hai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yang Hai

This figure shows the co-authorship network connecting the top 25 collaborators of Yang Hai. A scholar is included among the top collaborators of Yang Hai 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 Yang Hai. Yang Hai 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.
Hua, Rong, et al.. (2025). Substance P and neurokinin 1 receptor boost the pathogenicity of granulocyte‐macrophage colony‐stimulating factor‐producing T helper cells in dry eye disease. Scandinavian Journal of Immunology. 101(1). e13434–e13434. 1 indexed citations
2.
Li, Qing, Yang Hai, Tan Chen, et al.. (2024). Multi-omics approaches to understand pathogenicity during potato early blight disease caused by Alternaria solani. Frontiers in Microbiology. 15. 1357579–1357579. 3 indexed citations
3.
Zhang, Jieyun, Guanna Li, Jin Xie, et al.. (2024). Controllable Active Intermediate in CO2 Hydrogenation Enabling Highly Selective N,N-Dimethylformamide Synthesis via N-Formylation. Journal of the American Chemical Society. 147(4). 3152–3160. 7 indexed citations
4.
Hai, Yang, Jixiang Ma, Kaixin Yang, & Yalu Wen. (2023). Bayesian linear mixed model with multiple random effects for prediction analysis on high-dimensional multi-omics data. Bioinformatics. 39(11). 2 indexed citations
5.
Hua, Rong, et al.. (2022). Low Level of PALMD Contributes to the Metastasis of Uveal Melanoma. Frontiers in Oncology. 12. 802941–802941. 5 indexed citations
6.
Zhou, Rui, Dong Liu, Min Cui, et al.. (2021). Association Between Metabolic Syndrome and Mild Parkinsonian Signs Progression in the Elderly. Frontiers in Aging Neuroscience. 13. 722836–722836. 10 indexed citations
7.
Wang, Wenzhao, Jun Li, Lei Liu, et al.. (2021). Role of circular RNA expression in the pathological progression after spinal cord injury. Neural Regeneration Research. 16(10). 2048–2048. 22 indexed citations
8.
Chen, Yang, Huiyun Li, Fan Zeng, et al.. (2020). LincRNA Plays a Role in the Effect of CYP46A1 Polymorphism in Alzheimer’s Disease – Related Pathology. Frontiers in Aging Neuroscience. 11. 381–381. 8 indexed citations
9.
Hai, Yang & Yalu Wen. (2020). A Bayesian linear mixed model for prediction of complex traits. Bioinformatics. 36(22-23). 5415–5423. 2 indexed citations
10.
Huo, Yingchao, Jingjing Ma, Dong Liu, et al.. (2020). White matter hyperintensities and the progression from mild parkinsonian signs to parkinsonism and Parkinson’s disease. Neurobiology of Aging. 96. 267–276. 9 indexed citations
11.
Wang, Quan, Rui Chen, Feixiong Cheng, et al.. (2019). A Bayesian framework that integrates multi-omics data and gene networks predicts risk genes from schizophrenia GWAS data. Nature Neuroscience. 22(5). 691–699. 84 indexed citations
12.
Hai, Yang, et al.. (2019). De novo copy number variants and parental age: Is there an association?. European Journal of Medical Genetics. 63(4). 103829–103829. 5 indexed citations
13.
Chen, Le, et al.. (2019). Effects of Metabolic Syndrome on Cognitive Impairment with White Matter Lesions. European Neurology. 82(4-6). 99–105. 2 indexed citations
14.
Hai, Yang, et al.. (2019). Bone mass density and bone metabolism marker are associated with progression of carotid and cardiac calcified plaque in Chinese elderly population. Osteoporosis International. 30(9). 1807–1815. 13 indexed citations
15.
Chen, Jie, et al.. (2017). The 100 most influential papers about cataract surgery: a bibliometric analysis. International Journal of Ophthalmology. 10(10). 1586–1591. 7 indexed citations
16.
Hai, Yang, Qiang Wei, Xue Zhong, Hushan Yang, & Bingshan Li. (2016). Cancer driver gene discovery through an integrative genomics approach in a non-parametric Bayesian framework. Bioinformatics. 33(4). 483–490. 21 indexed citations
17.
Gao, Chuan, Nan Wang, Xiuqing Guo, et al.. (2015). A Comprehensive Analysis of Common and Rare Variants to Identify Adiposity Loci in Hispanic Americans: The IRAS Family Study (IRASFS). PLoS ONE. 10(11). e0134649–e0134649. 18 indexed citations
18.
Kuo, Jane Z., Xiuqing Guo, Ronald Klein, et al.. (2015). Adiponectin, Insulin Sensitivity and Diabetic Retinopathy in Latinos With Type 2 Diabetes. The Journal of Clinical Endocrinology & Metabolism. 100(9). 3348–3355. 24 indexed citations
19.
Hai, Yang. (2009). The relationship among gestational diabetes mellitus,serum selenium level and glutathione peroxidase activity. Zhongguo fuyou baojian. 1 indexed citations
20.
Wu, Zhenhua, Ningli Wang, & Yang Hai. (1997). [The primary study of ultrasound biomicroscope in imaging anterior segment tumors of eye].. PubMed. 13(4). 189–91. 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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