Danyao Jin

2.1k total citations · 1 hit paper
10 papers, 1.4k citations indexed

About

Danyao Jin is a scholar working on Surgery, Cardiology and Cardiovascular Medicine and Molecular Biology. According to data from OpenAlex, Danyao Jin has authored 10 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Surgery, 3 papers in Cardiology and Cardiovascular Medicine and 2 papers in Molecular Biology. Recurrent topics in Danyao Jin's work include Metabolomics and Mass Spectrometry Studies (2 papers), Diabetes, Cardiovascular Risks, and Lipoproteins (2 papers) and Cardiovascular Disease and Adiposity (2 papers). Danyao Jin is often cited by papers focused on Metabolomics and Mass Spectrometry Studies (2 papers), Diabetes, Cardiovascular Risks, and Lipoproteins (2 papers) and Cardiovascular Disease and Adiposity (2 papers). Danyao Jin collaborates with scholars based in United Kingdom, China and Malaysia. Danyao Jin's co-authors include Pei Gao, Xun Tang, Yonghua Hu, Dudan Zhang, Zhenping Zhao, Qian Deng, Zhengjing Huang, Li Y, Xueying Qin and Limin Wang and has published in prestigious journals such as JAMA, International Journal of Epidemiology and Nutrients.

In The Last Decade

Danyao Jin

10 papers receiving 1.4k citations

Hit Papers

Prevalence and Ethnic Pattern of Diabetes and Prediabetes... 2017 2026 2020 2023 2017 400 800 1.2k

Peers

Danyao Jin
Yu Mi Kang South Korea
Kwang Joon Kim South Korea
You‐Bin Lee South Korea
Danyao Jin
Citations per year, relative to Danyao Jin Danyao Jin (= 1×) peers Dudan Zhang

Countries citing papers authored by Danyao Jin

Since Specialization
Citations

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

Fields of papers citing papers by Danyao Jin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Danyao Jin

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

All Works

10 of 10 papers shown
1.
Jin, Danyao, Eirini Trichia, Nazrul Islam, et al.. (2023). Lipoprotein Characteristics and Incident Coronary Heart Disease: Prospective Cohort of Nearly 90 000 Individuals in UK Biobank. Journal of the American Heart Association. 12(20). e029552–e029552. 7 indexed citations
2.
Jin, Danyao, Eirini Trichia, Nazrul Islam, Sarah Lewington, & Ben Lacey. (2023). Predictive value of metabolic profiling in cardiovascular risk scores: analysis of 75 000 adults in UK Biobank. Journal of Epidemiology & Community Health. 77(12). 802–808. 2 indexed citations
3.
Trichia, Eirini, Deborah E. Malden, Danyao Jin, et al.. (2023). Independent relevance of adiposity measures to coronary heart disease risk among 0.5 million adults in UK Biobank. International Journal of Epidemiology. 52(6). 1836–1844. 1 indexed citations
4.
Jin, Danyao, Eirini Trichia, Nazrul Islam, Sarah Lewington, & Ben Lacey. (2023). Associations of circulating fatty acids with incident coronary heart disease: a prospective study of 89,242 individuals in UK Biobank. BMC Cardiovascular Disorders. 23(1). 365–365. 7 indexed citations
5.
Oguntade, Ayodipupo Sikiru, Nazrul Islam, Reem Malouf, et al.. (2023). Body Composition and Risk of Incident Heart Failure in 1 Million Adults: A Systematic Review and Dose–Response Meta‐Analysis of Prospective Cohort Studies. Journal of the American Heart Association. 12(13). e029062–e029062. 18 indexed citations
6.
Tang, Xun, Ke Lü, Danyao Jin, et al.. (2021). Incidence and Survival of Aortic Dissection in Urban China: Results from the National Insurance Claims for Epidemiological Research (NICER) Study. The Lancet Regional Health - Western Pacific. 17. 100280–100280. 29 indexed citations
7.
Oguntade, Ayodipupo Sikiru, Danyao Jin, Nazrul Islam, et al.. (2021). Body composition and risk of heart failure: protocol for a systematic review and meta-analysis. Open Heart. 8(1). e001632–e001632. 3 indexed citations
8.
Jin, Danyao, Janet W. Rich‐Edwards, Yue Huang, et al.. (2020). Gestational Diabetes Mellitus: Predictive Value of Fetal Growth Measurements by Ultrasonography at 22–24 Weeks: A Retrospective Cohort Study of Medical Records. Nutrients. 12(12). 3645–3645. 10 indexed citations
9.
Zhang, Dudan, Xun Tang, Danyao Jin, Yonghua Hu, & Pei Gao. (2018). [Prevalence of diabetes in Chinese adults: a Meta-analysis].. PubMed. 39(6). 852–857. 11 indexed citations
10.
Wang, Limin, Pei Gao, Mei Zhang, et al.. (2017). Prevalence and Ethnic Pattern of Diabetes and Prediabetes in China in 2013. JAMA. 317(24). 2515–2515. 1340 indexed citations breakdown →

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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