Shan‐Shan Dong

6.2k total citations · 2 hit papers
121 papers, 3.7k citations indexed

About

Shan‐Shan Dong is a scholar working on Molecular Biology, Genetics and Cancer Research. According to data from OpenAlex, Shan‐Shan Dong has authored 121 papers receiving a total of 3.7k indexed citations (citations by other indexed papers that have themselves been cited), including 58 papers in Molecular Biology, 34 papers in Genetics and 17 papers in Cancer Research. Recurrent topics in Shan‐Shan Dong's work include Genetic Associations and Epidemiology (25 papers), Cancer-related molecular mechanisms research (14 papers) and RNA modifications and cancer (11 papers). Shan‐Shan Dong is often cited by papers focused on Genetic Associations and Epidemiology (25 papers), Cancer-related molecular mechanisms research (14 papers) and RNA modifications and cancer (11 papers). Shan‐Shan Dong collaborates with scholars based in China, United States and United Kingdom. Shan‐Shan Dong's co-authors include Tie‐Lin Yang, Weiming He, Chi Zhang, Junyang Xu, Yan Guo, Hong‐Wen Deng, Jingjing Ji, Chi Zhang, Hui Shen and Shi Yao and has published in prestigious journals such as Nature Communications, Nature Neuroscience and Bioinformatics.

In The Last Decade

Shan‐Shan Dong

113 papers receiving 3.6k citations

Hit Papers

PopLDdecay: a fast and effective tool for linkage disequi... 2018 2026 2020 2023 2018 2020 250 500 750 1000

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Shan‐Shan Dong China 29 1.4k 1.3k 691 439 221 121 3.7k
Tie‐Lin Yang China 33 1.8k 1.3× 2.1k 1.5× 702 1.0× 552 1.3× 198 0.9× 149 4.5k
Bin Tang China 42 1.1k 0.8× 2.4k 1.8× 518 0.7× 770 1.8× 273 1.2× 157 5.0k
Lingli Zhang China 37 285 0.2× 2.8k 2.1× 1.1k 1.6× 579 1.3× 212 1.0× 206 5.2k
Jun Zhang China 39 1.1k 0.8× 3.0k 2.3× 798 1.2× 382 0.9× 482 2.2× 277 6.6k
Valentina Gatta Italy 38 1.5k 1.1× 1.8k 1.3× 157 0.2× 234 0.5× 301 1.4× 158 4.1k
Anne De Paepe Belgium 19 1.2k 0.9× 2.4k 1.8× 773 1.1× 438 1.0× 345 1.6× 36 4.7k
Tatsuya Yoshizawa Japan 36 1.1k 0.8× 2.9k 2.2× 836 1.2× 410 0.9× 324 1.5× 105 6.8k
Aleš Tichopád Czechia 19 688 0.5× 3.9k 2.9× 655 0.9× 620 1.4× 376 1.7× 57 6.1k
Hao Feng China 27 338 0.3× 1.4k 1.1× 442 0.6× 251 0.6× 251 1.1× 107 2.8k

Countries citing papers authored by Shan‐Shan Dong

Since Specialization
Citations

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

Fields of papers citing papers by Shan‐Shan Dong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Shan‐Shan Dong. 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 Shan‐Shan Dong. The network helps show where Shan‐Shan Dong may publish in the future.

Co-authorship network of co-authors of Shan‐Shan Dong

This figure shows the co-authorship network connecting the top 25 collaborators of Shan‐Shan Dong. A scholar is included among the top collaborators of Shan‐Shan Dong 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 Shan‐Shan Dong. Shan‐Shan Dong 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.
Li, Na, et al.. (2025). Can mixed-ownership reform in state-owned enterprises promote urban green transformation? Evidence from Chinese cities. Journal of Cleaner Production. 519. 145923–145923. 3 indexed citations
4.
Su, Jie, Kuishuang Shao, Shan‐Shan Dong, et al.. (2024). Microbial degradation of DOC released by the mixed culture of Crassostrea gigas and Undaria pinnatifida. Regional Studies in Marine Science. 79. 103800–103800. 1 indexed citations
5.
Zhang, Yan, Xin‐Hao Li, Zihan Qiu, et al.. (2024). RUNX2 Phase Separation Mediates Long‐Range Regulation Between Osteoporosis‐Susceptibility Variant and XCR1 to Promote Osteoblast Differentiation. Advanced Science. 12(6). e2413561–e2413561. 1 indexed citations
6.
Tang, Guangbo, Zhangqian Chen, Zihang Li, et al.. (2024). Neutrophil-centric analysis of gastric cancer: prognostic modeling and molecular insights. Cellular and Molecular Life Sciences. 81(1). 452–452. 5 indexed citations
7.
Zhang, Kun, Pengfei Wang, Wei Huang, et al.. (2024). Integrated landscape of plasma metabolism and proteome of patients with post-traumatic deep vein thrombosis. Nature Communications. 15(1). 7831–7831. 9 indexed citations
8.
Dong, Shan‐Shan, Zhijun Tang, & Huadóng Ma. (2024). A Review Of Routing Protocols For FANET. IOSR Journal of Electronics and Communication Engineering. 19(6). 6–22.
9.
Wang, Naining, Yan Zhang, Feng Jiang, et al.. (2023). Enhancer variants on chromosome 2p14 regulating SPRED2 and ACTR2 act as a signal amplifier to protect against rheumatoid arthritis. The American Journal of Human Genetics. 110(4). 625–637. 5 indexed citations
10.
Wu, Hao, Wei Huang, Shi Yao, et al.. (2022). Multitissue Integrative Analysis Identifies Susceptibility Genes for Atopic Dermatitis. Journal of Investigative Dermatology. 143(4). 602–611.e14. 7 indexed citations
12.
Yao, Shi, Hao Wu, Tong‐Tong Liu, et al.. (2021). Epigenetic Element-Based Transcriptome-Wide Association Study Identifies Novel Genes for Bipolar Disorder. Schizophrenia Bulletin. 47(6). 1642–1652. 10 indexed citations
13.
Zhang, Kun, Shan‐Shan Dong, Yan Guo, et al.. (2021). Causal Associations Between Blood Lipids and COVID-19 Risk: A Two-Sample Mendelian Randomization Study. Arteriosclerosis Thrombosis and Vascular Biology. 41(11). 2802–2810. 13 indexed citations
14.
Dong, Shan‐Shan, Weiming He, Jingjing Ji, et al.. (2020). LDBlockShow: a fast and convenient tool for visualizing linkage disequilibrium and haplotype blocks based on variant call format files. Briefings in Bioinformatics. 22(4). 298 indexed citations breakdown →
15.
Chen, Xiaofeng, Wei‐Xin Hu, Yuanyuan Duan, et al.. (2019). An Allele-Specific Functional SNP Associated with Two Systemic Autoimmune Diseases Modulates IRF5 Expression by Long-Range Chromatin Loop Formation. Journal of Investigative Dermatology. 140(2). 348–360.e11. 25 indexed citations
16.
Zhou, Linghui, Shan‐Shan Dong, Yujiao Deng, et al.. (2019). GOLGA7 rs11337, a Polymorphism at the MicroRNA Binding Site, Is Associated with Glioma Prognosis. Molecular Therapy — Nucleic Acids. 18. 56–65. 13 indexed citations
17.
Zhang, Chi, Shan‐Shan Dong, Junyang Xu, Weiming He, & Tie‐Lin Yang. (2018). PopLDdecay: a fast and effective tool for linkage disequilibrium decay analysis based on variant call format files. Bioinformatics. 35(10). 1786–1788. 1079 indexed citations breakdown →
18.
Dong, Shan‐Shan, et al.. (2016). The impact of abacus training on working memory and underlying neural correlates in young adults. Neuroscience. 332. 181–190. 31 indexed citations
19.
Dong, Shan‐Shan, Xuemei Zhang, Yujuan He, et al.. (2013). Synergy of IL-27 and TNF-α in Regulating CXCL10 Expression in Lung Fibroblasts. American Journal of Respiratory Cell and Molecular Biology. 48(4). 518–530. 40 indexed citations
20.
Wang, Jin‐Tang, Yan Guo, Tie‐Lin Yang, et al.. (2008). Polymorphisms in the estrogen receptor genes are associated with hip fractures in Chinese. Bone. 43(5). 910–914. 15 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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