Hui Tan

956 total citations
21 papers, 618 citations indexed

About

Hui Tan is a scholar working on Molecular Biology, Cancer Research and Epidemiology. According to data from OpenAlex, Hui Tan has authored 21 papers receiving a total of 618 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Molecular Biology, 5 papers in Cancer Research and 3 papers in Epidemiology. Recurrent topics in Hui Tan's work include MicroRNA in disease regulation (4 papers), RNA modifications and cancer (4 papers) and RNA Research and Splicing (3 papers). Hui Tan is often cited by papers focused on MicroRNA in disease regulation (4 papers), RNA modifications and cancer (4 papers) and RNA Research and Splicing (3 papers). Hui Tan collaborates with scholars based in China, Singapore and Israel. Hui Tan's co-authors include Weiping Li, Wenlan Liu, Jing Quan, Chun Loong Ho, Khoon Lin Ling, Yung Seng Lee, Aram Kang, Matthew Wook Chang, Koon Jiew Chua and Kiat Hon Lim and has published in prestigious journals such as Nature Communications, Molecular Cell and Scientific Reports.

In The Last Decade

Hui Tan

21 papers receiving 608 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Hui Tan China 13 393 185 99 84 81 21 618
Wujiao Li China 14 245 0.6× 127 0.7× 41 0.4× 137 1.6× 52 0.6× 30 612
Elena Garré Sweden 14 507 1.3× 136 0.7× 25 0.3× 92 1.1× 40 0.5× 22 673
Søren Carlsen Denmark 7 356 0.9× 82 0.4× 96 1.0× 45 0.5× 20 0.2× 11 578
Xian Jia China 8 401 1.0× 33 0.2× 38 0.4× 32 0.4× 104 1.3× 14 576
Xiaojie Wu China 15 284 0.7× 63 0.3× 17 0.2× 104 1.2× 43 0.5× 35 528
Dilani G. Gamage United States 9 608 1.5× 41 0.2× 25 0.3× 36 0.4× 55 0.7× 12 738
Steven Szarka Canada 8 356 0.9× 44 0.2× 239 2.4× 26 0.3× 36 0.4× 8 509
Georgij Arapidi Russia 15 405 1.0× 108 0.6× 12 0.1× 30 0.4× 65 0.8× 54 672
Linhong Li United States 16 571 1.5× 86 0.5× 45 0.5× 67 0.8× 251 3.1× 35 924
James T. Neal United States 7 408 1.0× 71 0.4× 18 0.2× 40 0.5× 157 1.9× 8 652

Countries citing papers authored by Hui Tan

Since Specialization
Citations

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

Fields of papers citing papers by Hui Tan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hui Tan

This figure shows the co-authorship network connecting the top 25 collaborators of Hui Tan. A scholar is included among the top collaborators of Hui Tan 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 Hui Tan. Hui Tan 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.
Tan, Hui, et al.. (2024). Original investigation: manipulating energy availability in male endurance runners: a randomised controlled trial. Applied Physiology Nutrition and Metabolism. 49(9). 1163–1174. 1 indexed citations
2.
Jin, Wenhao, Kristopher W. Brannan, Katannya Kapeli, et al.. (2023). HydRA: Deep-learning models for predicting RNA-binding capacity from protein interaction association context and protein sequence. Molecular Cell. 83(14). 2595–2611.e11. 17 indexed citations
3.
Cui, Jianzhou, et al.. (2023). The ER-Golgi transport of influenza virus through NS1-Sec13 association during virus replication. Microbiology Spectrum. 12(1). e0260923–e0260923. 1 indexed citations
4.
Zhang, He, Haojun Yu, Hui Tan, et al.. (2022). An initial study on the comparison of diagnostic performance of 18F-FDG PET/MR and 18F-FDG PET/CT for thoracic staging of non-small cell lung cancer: Focus on pleural invasion. Revista Española de Medicina Nuclear e Imagen Molecular (English Edition). 42(1). 16–23. 8 indexed citations
5.
Han, Jian, Ömer An, Xi Ren, et al.. (2022). Multilayered control of splicing regulatory networks by DAP3 leads to widespread alternative splicing changes in cancer. Nature Communications. 13(1). 1793–1793. 15 indexed citations
7.
Han, Jian, Ömer An, HuiQi Hong, et al.. (2020). Suppression of adenosine-to-inosine (A-to-I) RNA editome by death associated protein 3 (DAP3) promotes cancer progression. Science Advances. 6(25). eaba5136–eaba5136. 32 indexed citations
8.
Tan, Hui, et al.. (2019). Alternative Experimental Models for Studying Influenza Proteins, Host–Virus Interactions and Anti-Influenza Drugs. Pharmaceuticals. 12(4). 147–147. 15 indexed citations
9.
Ren, Li, Conghui Yang, Hui Tan, et al.. (2018). Comparison of diploid and triploid Carassius auratus provides insights into adaptation to environmental change. Science China Life Sciences. 61(11). 1407–1419. 9 indexed citations
10.
Xu, Yanwen, Renli Liu, Jing Liu, et al.. (2018). High expression of immunity-related GTPase family M protein in glioma promotes cell proliferation and autophagy protein expression. Pathology - Research and Practice. 215(1). 90–96. 7 indexed citations
11.
Ho, Chun Loong, Hui Tan, Koon Jiew Chua, et al.. (2018). Engineered commensal microbes for diet-mediated colorectal-cancer chemoprevention. Nature Biomedical Engineering. 2(1). 27–37. 218 indexed citations
12.
Li, Wuhui, Hui Tan, Conghui Yang, et al.. (2018). Genetic Effects on the Gut Microbiota Assemblages of Hybrid Fish From Parents With Different Feeding Habits. Frontiers in Microbiology. 9. 2972–2972. 48 indexed citations
13.
Li, Wuhui, Junmei Liu, Hui Tan, et al.. (2018). Asymmetric expression patterns reveal a strong maternal effect and dosage compensation in polyploid hybrid fish. BMC Genomics. 19(1). 517–517. 18 indexed citations
15.
Liu, Jing, et al.. (2018). MicroRNAs as potential biomarkers for the diagnosis of glioma: A systematic review and meta‐analysis. Cancer Science. 109(9). 2651–2659. 117 indexed citations
16.
Li, Wuhui, Hui Tan, Junmei Liu, et al.. (2018). Comparative analysis of testis transcriptomes associated with male infertility in triploid cyprinid fish. Reproduction Fertility and Development. 31(2). 248–260. 15 indexed citations
17.
Xu, Yanwen, Renli Liu, Jing Liu, et al.. (2018). IRGM promotes glioma M2 macrophage polarization through p62/TRAF6/NF‐κB pathway mediated IL‐8 production. Cell Biology International. 43(2). 125–135. 36 indexed citations
18.
Li, Ren, Jialin Cui, Jing Wang, et al.. (2017). Analyzing homoeolog expression provides insights into the rediploidization event in gynogenetic hybrids of Carassius auratus red var. × Cyprinus carpio. Scientific Reports. 7(1). 13679–13679. 14 indexed citations
19.
Yang, Kaiyun, Hui Tan, Anning Chen, et al.. (2017). Expression of PANDA, LincRNA-p21, PUMA in lung tissues of lung cancer patients in the Xuanwei and non-Xuanwei areas of Yunnan Province. Journal of Cancer Metastasis and Treatment. 3(3). 65–65. 1 indexed citations
20.
Chen, Jianjun, et al.. (2006). [The concentration and expression of IL-4, IL-5, IL-6, IL-8 in human nasal polyps tissues].. PubMed. 20(11). 484–6. 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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