Yan Si

644 total citations
27 papers, 452 citations indexed

About

Yan Si is a scholar working on Radiology, Nuclear Medicine and Imaging, Endocrinology, Diabetes and Metabolism and Biomedical Engineering. According to data from OpenAlex, Yan Si has authored 27 papers receiving a total of 452 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Radiology, Nuclear Medicine and Imaging, 9 papers in Endocrinology, Diabetes and Metabolism and 9 papers in Biomedical Engineering. Recurrent topics in Yan Si's work include Advanced X-ray and CT Imaging (9 papers), Thyroid Cancer Diagnosis and Treatment (9 papers) and Radiation Dose and Imaging (8 papers). Yan Si is often cited by papers focused on Advanced X-ray and CT Imaging (9 papers), Thyroid Cancer Diagnosis and Treatment (9 papers) and Radiation Dose and Imaging (8 papers). Yan Si collaborates with scholars based in China and United States. Yan Si's co-authors include Meiping Shen, Yan Zhou, Xiao‐Quan Xu, Guo‐Yi Su, Xi Zhuang, Hao Zhang, Yang Zhou, Jing‐Yuan Xu, Bo Yu and Zhijun Min and has published in prestigious journals such as Scientific Reports, Applied Microbiology and Biotechnology and Cell Death and Disease.

In The Last Decade

Yan Si

23 papers receiving 447 citations

Peers

Yan Si
Denghua Pan China
Yinlong Yang China
Daiki Ueno Japan
Hyeong Ju Kwon South Korea
Dingcun Luo China
Hailong Chen China
Reza Golestani United States
Danila Serpico Italy
Fatiha Merabtene France
Denghua Pan China
Yan Si
Citations per year, relative to Yan Si Yan Si (= 1×) peers Denghua Pan

Countries citing papers authored by Yan Si

Since Specialization
Citations

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

Fields of papers citing papers by Yan Si

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yan Si

This figure shows the co-authorship network connecting the top 25 collaborators of Yan Si. A scholar is included among the top collaborators of Yan Si 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 Yan Si. Yan Si 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.
Zhang, Lijun, Chengyuan Li, Jianing Zhou, et al.. (2025). UBE2T promotes papillary thyroid carcinoma progression by activating the JAK/STAT3 pathway via negative regulation of SOCS2. Seminars in Oncology. 53(1). 152439–152439.
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Wang, Ying, et al.. (2024). Preoperative ultrasound-guided injection of nanocarbon for central lymph node dissection in patients with papillary thyroid carcinoma. Scientific Reports. 14(1). 29185–29185. 1 indexed citations
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Xu, Xiao‐Quan, et al.. (2022). Iodine Maps from Dual-Energy CT to Predict Extrathyroidal Extension and Recurrence in Papillary Thyroid Cancer Based on a Radiomics Approach. American Journal of Neuroradiology. 43(5). 748–755. 15 indexed citations
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Wang, Xiaoting, et al.. (2022). Proactive exploration of inferior parathyroid gland using a novel meticulous thyrothymic ligament dissection technique. European Journal of Surgical Oncology. 48(6). 1258–1263. 1 indexed citations
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Zhou, Yan, Guo‐Yi Su, Hao Hu, et al.. (2021). Radiomics from Primary Tumor on Dual-Energy CT Derived Iodine Maps can Predict Cervical Lymph Node Metastasis in Papillary Thyroid Cancer. Academic Radiology. 29. S222–S231. 21 indexed citations
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Zhou, Yang, Xiyi Wei, Jing‐Yuan Xu, et al.. (2021). A new risk factor indicator for papillary thyroid cancer based on immune infiltration. Cell Death and Disease. 12(1). 51–51. 78 indexed citations
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Si, Yan, et al.. (2021). An Anti-EGFR/anti- HER2 Bispecific Antibody with Enhanced Antitumor Activity Against Acquired Gefitinib-Resistant NSCLC Cells. Protein and Peptide Letters. 28(11). 1290–1297. 7 indexed citations
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Ding, Yu, Luyao Wu, Xi Zhuang, et al.. (2021). The direct miR‐874‐3p‐target FAM84A promotes tumor development in papillary thyroid cancer. Molecular Oncology. 15(5). 1597–1614. 12 indexed citations
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Wu, Luyao, Yu Ding, Xi Zhuang, et al.. (2021). Long noncoding RNA FER1L4 promotes the malignant processes of papillary thyroid cancer by targeting the miR-612/ Cadherin 4 axis. Cancer Cell International. 21(1). 392–392. 7 indexed citations
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Zhou, Yan, Guo‐Yi Su, Hao Hu, et al.. (2020). Radiomics analysis of dual-energy CT-derived iodine maps for diagnosing metastatic cervical lymph nodes in patients with papillary thyroid cancer. European Radiology. 30(11). 6251–6262. 61 indexed citations
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Zhuang, Xi, et al.. (2019). <p>Long noncoding RNA ZFAS1 promotes progression of papillary thyroid carcinoma by sponging miR-590-3p and upregulating HMGA2 expression</p>. OncoTargets and Therapy. Volume 12. 7501–7512. 30 indexed citations
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Xu, Changzhi, Qianqian Han, Qin Zhou, et al.. (2019). MiR-106b promotes therapeutic antibody expression in CHO cells by targeting deubiquitinase CYLD. Applied Microbiology and Biotechnology. 103(17). 7085–7095. 10 indexed citations
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Si, Yan. (2009). Central pontine myelinolysis after liver transplantation:5 cases report. 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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2026