Hong Sun

5.2k total citations · 2 hit papers
64 papers, 2.8k citations indexed

About

Hong Sun is a scholar working on Molecular Biology, Obstetrics and Gynecology and Cancer Research. According to data from OpenAlex, Hong Sun has authored 64 papers receiving a total of 2.8k indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Molecular Biology, 13 papers in Obstetrics and Gynecology and 10 papers in Cancer Research. Recurrent topics in Hong Sun's work include Gestational Diabetes Research and Management (11 papers), Pregnancy and preeclampsia studies (5 papers) and MicroRNA in disease regulation (5 papers). Hong Sun is often cited by papers focused on Gestational Diabetes Research and Management (11 papers), Pregnancy and preeclampsia studies (5 papers) and MicroRNA in disease regulation (5 papers). Hong Sun collaborates with scholars based in China, Belgium and United States. Hong Sun's co-authors include Suvi Karuranga, Dianna J. Magliano, Noël C. Barengo, Julian W. Sacre, Leonor Guariguata, Paz Lopez‐Doriga Ruiz, Katherine Ogurtsova, Edward J. Boyko, Haiyan Zhang and David Simmons and has published in prestigious journals such as SHILAP Revista de lepidopterología, Nano Letters and Bioinformatics.

In The Last Decade

Hong Sun

62 papers receiving 2.7k citations

Hit Papers

IDF Diabetes Atlas: Estim... 2021 2026 2022 2024 2021 2021 200 400 600

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Hong Sun China 27 816 673 442 350 297 64 2.8k
Karina Braga Gomes Brazil 31 850 1.0× 713 1.1× 431 1.0× 327 0.9× 461 1.6× 194 3.8k
Claudio Aguayo Chile 24 740 0.9× 354 0.5× 710 1.6× 343 1.0× 251 0.8× 71 2.9k
Asad Vaisi‐Raygani Iran 29 548 0.7× 219 0.3× 292 0.7× 189 0.5× 226 0.8× 157 2.5k
Valeska Ormazábal Chile 19 783 1.0× 281 0.4× 666 1.5× 273 0.8× 104 0.4× 32 2.5k
Xin Zhou China 31 1.3k 1.6× 252 0.4× 192 0.4× 561 1.6× 192 0.6× 175 3.7k
Mitsuhiro Nakamura Japan 37 1.4k 1.7× 272 0.4× 167 0.4× 196 0.6× 180 0.6× 198 4.0k
Tomohiro Nakayama Japan 30 958 1.2× 141 0.2× 766 1.7× 430 1.2× 185 0.6× 223 3.6k
Woong Ju South Korea 27 738 0.9× 547 0.8× 95 0.2× 304 0.9× 95 0.3× 99 3.0k
Keiichi Kodama United States 19 721 0.9× 284 0.4× 978 2.2× 698 2.0× 166 0.6× 31 2.9k

Countries citing papers authored by Hong Sun

Since Specialization
Citations

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

Fields of papers citing papers by Hong Sun

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hong Sun

This figure shows the co-authorship network connecting the top 25 collaborators of Hong Sun. A scholar is included among the top collaborators of Hong Sun 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 Sun. Hong Sun 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
2.
Sun, Hong, Kun Liu, Jinqiu Fu, et al.. (2025). Establishment of ABEI-based direct chemiluminescence immunoassays for PIC, TAT, tPAIC, and TM and their preliminary evaluation in thrombotic diseases. Analytical Methods. 17(26). 5489–5497. 1 indexed citations
3.
Wu, Xiaomei, Shuo Zhang, Mei Feng, et al.. (2024). Glutathione Induced In Situ Activation of Dual‐Locked Cuproptosis Nanoamplifier with Glycolysis Metabolism Inhibition to Boost Cancer Immunotherapy. Advanced Healthcare Materials. 14(4). e2403380–e2403380. 6 indexed citations
4.
Dong, Hongli, Hong Sun, Sijia Chen, et al.. (2022). Dietary fat quantity and quality in early pregnancy and risk of gestational diabetes mellitus in Chinese women: a prospective cohort study. British Journal Of Nutrition. 129(9). 1481–1490. 4 indexed citations
5.
Harding, Jessica L., Pandora L. Wander, Xinge Zhang, et al.. (2022). The Incidence of Adult-Onset Type 1 Diabetes: A Systematic Review From 32 Countries and Regions. Diabetes Care. 45(4). 994–1006. 76 indexed citations
6.
Sun, Hong, Hongli Dong, Yiqi Zhang, et al.. (2021). Specific fruit but not total fruit intake during early pregnancy is inversely associated with gestational diabetes mellitus risk: a prospective cohort study. Public Health Nutrition. 24(13). 4054–4063. 7 indexed citations
7.
Wang, Hui, Ninghua Li, Tawanda Chivese, et al.. (2021). IDF Diabetes Atlas: Estimation of Global and Regional Gestational Diabetes Mellitus Prevalence for 2021 by International Association of Diabetes in Pregnancy Study Group’s Criteria. Diabetes Research and Clinical Practice. 183. 109050–109050. 633 indexed citations breakdown →
9.
Zhang, Yan, Xinyi Tan, Tianyang Ren, et al.. (2018). Folate-modified carboxymethyl-chitosan/polyethylenimine/bovine serum albumin based complexes for tumor site-specific drug delivery. Carbohydrate Polymers. 198. 76–85. 26 indexed citations
10.
Tang, Qiuqin, Jing Li, Simin Zhang, et al.. (2013). GSTM1 and GSTT1 Null Polymorphisms and Childhood Acute Leukemia Risk: Evidence from 26 Case-Control Studies. PLoS ONE. 8(10). e78810–e78810. 10 indexed citations
11.
Lv, Qiang, et al.. (2013). Association of the methylenetetrahydrofolate reductase gene A1298C polymorphism with stroke risk based on a meta-analysis. Genetics and Molecular Research. 12(4). 6882–6894. 13 indexed citations
13.
Zhang, Xiaoyan, Jun Chen, Yu Kang, et al.. (2013). Targeted paclitaxel nanoparticles modified with follicle-stimulating hormone β 81–95 peptide show effective antitumor activity against ovarian carcinoma. International Journal of Pharmaceutics. 453(2). 498–505. 31 indexed citations
14.
Li, Lijuan, Xiutian Sima, Peng Bai, et al.. (2012). Interactions ofmiR-34b/candTP53Polymorphisms on the Risk of Intracranial Aneurysm. SHILAP Revista de lepidopterología. 2012. 1–7. 26 indexed citations
15.
Zhong, Weiying, Xiutian Sima, Siqing Huang, et al.. (2012). Traumatic extradural hematoma in childhood. Child s Nervous System. 29(4). 635–641. 10 indexed citations
17.
Shi, Fang, Xuelian Zheng, Qiong Wang, et al.. (2011). Crocetin induces cytotoxicity and enhances vincristine-induced cancer cell death via p53-dependent and -independent mechanisms. Acta Pharmacologica Sinica. 32(12). 1529–1536. 36 indexed citations
18.
Wang, Qiong, Lan Yang, Fang Shi, et al.. (2010). Reactive oxygen species-mediated apoptosis contributes to chemosensitization effect of saikosaponins on cisplatin-induced cytotoxicity in cancer cells. Journal of Experimental & Clinical Cancer Research. 29(1). 159–159. 104 indexed citations
19.
Zhang, Xiaoyan, Jun Chen, Yufang Zheng, et al.. (2009). Follicle-Stimulating Hormone Peptide Can Facilitate Paclitaxel Nanoparticles to Target Ovarian Carcinoma In vivo. Cancer Research. 69(16). 6506–6514. 80 indexed citations
20.
Sun, Hong, Jun Wang, Yu Shi, et al.. (2008). The Upregulation of Osteoblast Marker Genes in Mesenchymal Stem Cells Prove the Osteoinductivity of Hydroxyapatite/Tricalcium Phosphate Biomaterial. Transplantation Proceedings. 40(8). 2645–2648. 47 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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