Hui Tang

3.9k total citations
119 papers, 2.6k citations indexed

About

Hui Tang is a scholar working on Molecular Biology, Cancer Research and Genetics. According to data from OpenAlex, Hui Tang has authored 119 papers receiving a total of 2.6k indexed citations (citations by other indexed papers that have themselves been cited), including 62 papers in Molecular Biology, 29 papers in Cancer Research and 28 papers in Genetics. Recurrent topics in Hui Tang's work include Genetic and phenotypic traits in livestock (17 papers), MicroRNA in disease regulation (17 papers) and Cancer-related molecular mechanisms research (14 papers). Hui Tang is often cited by papers focused on Genetic and phenotypic traits in livestock (17 papers), MicroRNA in disease regulation (17 papers) and Cancer-related molecular mechanisms research (14 papers). Hui Tang collaborates with scholars based in China, United States and Singapore. Hui Tang's co-authors include Alfonso Eirin, Lilach O. Lerman, Xiang-Yang Zhu, Darrell W. Brann, Ruimin Wang, Yan Dong, Amir Lerman, Ren‐Cheng Tang, Surendra Dasari and André J. van Wijnen and has published in prestigious journals such as Journal of Clinical Oncology, Bioinformatics and PLoS ONE.

In The Last Decade

Hui Tang

116 papers receiving 2.5k 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 Tang China 28 1.1k 569 427 217 204 119 2.6k
Yong Shen China 20 678 0.6× 310 0.5× 325 0.8× 217 1.0× 43 0.2× 39 1.9k
Mei Zhu China 38 1.7k 1.5× 227 0.4× 254 0.6× 216 1.0× 188 0.9× 117 4.1k
Robert A. Frost United States 45 2.5k 2.3× 284 0.5× 260 0.6× 159 0.7× 102 0.5× 90 4.8k
Yang Chen China 27 1.6k 1.5× 954 1.7× 183 0.4× 275 1.3× 41 0.2× 170 3.3k
Li Yu China 30 1.4k 1.3× 409 0.7× 122 0.3× 94 0.4× 73 0.4× 85 2.8k
Hong Yu United States 30 1.1k 1.0× 202 0.4× 174 0.4× 308 1.4× 53 0.3× 126 2.9k
Yue Huang China 34 1.3k 1.1× 229 0.4× 195 0.5× 156 0.7× 239 1.2× 152 3.9k
Yijing Chen China 27 2.0k 1.8× 146 0.3× 456 1.1× 168 0.8× 69 0.3× 100 3.1k

Countries citing papers authored by Hui Tang

Since Specialization
Citations

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

Fields of papers citing papers by Hui Tang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hui Tang

This figure shows the co-authorship network connecting the top 25 collaborators of Hui Tang. A scholar is included among the top collaborators of Hui Tang 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 Tang. Hui Tang 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.
Li, Wenqiang, Huixin Liu, Fei Xu, et al.. (2025). Identification of key LncRNAs and mRNAs associated with intramuscular fat in pig via WGCNA. BMC Genomics. 26(1). 233–233.
2.
Krueger, Alexander, Xiangyang Zhu, Hui Tang, et al.. (2025). Mesenchymal Stem/Stromal Cells Reverse Adipose Tissue Inflammation in Pigs with Metabolic Syndrome and Renovascular Hypertension. Cells. 14(1). 40–40. 2 indexed citations
3.
Zhang, Jing, Hui Liu, Yang Shen, et al.. (2024). Macrophage AHR-TLR4 cross-talk drives p-STAT3 (Ser727)-mediated mitochondrial oxidative stress and upregulates IDO/ICAM-1 in the steatohepatitis induced by aflatoxin B1. The Science of The Total Environment. 923. 171377–171377. 6 indexed citations
4.
Li, Wenqiang, Xiaomin Li, Xuguang Zhang, et al.. (2024). Integrating Single-Cell RNA-Seq and ATAC-Seq Analysis Reveals Uterine Cell Heterogeneity and Regulatory Networks Linked to Pimpled Eggs in Chickens. International Journal of Molecular Sciences. 25(24). 13431–13431. 1 indexed citations
5.
Ma, Xueying, et al.. (2024). Synergistic cooperation between the β-catenin and SF1 regulates progesterone synthesis in laying hen ovarian granulosa cells. Animal Biotechnology. 35(1). 2351975–2351975. 1 indexed citations
6.
Wang, Dan, Jun Teng, Chao Ning, et al.. (2022). Mitogenome-wide association study on body measurement traits of Wenshang Barred chickens. Animal Biotechnology. 34(7). 3154–3161. 2 indexed citations
7.
Tang, Hui, et al.. (2021). Decoding Cinnabarinic Acid–Specific Stanniocalcin 2 Induction by Aryl Hydrocarbon Receptor. Molecular Pharmacology. 101(1). 45–55. 6 indexed citations
8.
Tang, Yunqiang, Shaoyan Xi, Jane Ho Chun Loong, et al.. (2021). Targeting tumor lineage plasticity in hepatocellular carcinoma using an anti-CLDN6 antibody-drug conjugate. Science Translational Medicine. 13(579). 54 indexed citations
9.
Wang, Dan, Hui Tang, Jianfeng Liu, et al.. (2020). Rapid epistatic mixed-model association studies by controlling multiple polygenic effects. Bioinformatics. 36(19). 4833–4837. 23 indexed citations
10.
Liu, Liying, et al.. (2019). Cecal CircRNAs Are Associated With the Response to Salmonella Enterica Serovar Enteritidis Inoculation in the Chicken. Frontiers in Immunology. 10. 1186–1186. 15 indexed citations
11.
Li, Wenting, et al.. (2019). A double-labeling marker-based method for estimating inbreeding and parental genomic components in a population under conservation. Asian-Australasian Journal of Animal Sciences. 33(1). 12–23. 2 indexed citations
12.
Li, Xiuxiu, et al.. (2018). Detection of KIT Genotype in Pigs by TaqMan MGB Real-Time Quantitative Polymerase Chain Reaction. DNA and Cell Biology. 37(5). 457–464. 6 indexed citations
13.
Le, Yong, Peng Jiang, Hui Tang, et al.. (2018). Aberrant MCT4 and GLUT1 expression is correlated with early recurrence and poor prognosis of hepatocellular carcinoma after hepatectomy. Cancer Medicine. 7(11). 5339–5350. 29 indexed citations
14.
Kang, Li, Chunhong Yang, Haizhen Wu, et al.. (2017). miR-26a-5p Regulates TNRC6A Expression and Facilitates Theca Cell Proliferation in Chicken Ovarian Follicles. DNA and Cell Biology. 36(11). 922–929. 31 indexed citations
15.
Kim, Sun-Yee, Choon Kiat Sim, Qiongyi Zhang, et al.. (2016). An Alternative Strategy for Pan-acetyl-lysine Antibody Generation. PLoS ONE. 11(9). e0162528–e0162528. 9 indexed citations
16.
17.
Tan, Xiang-Lin, Miao Shi, Hui Tang, Weiguo Han, & Simon D. Spivack. (2010). Candidate Dietary Phytochemicals Modulate Expression of Phase II Enzymes GSTP1 and NQO1 in Human Lung Cells , ,. Journal of Nutrition. 140(8). 1404–1410. 39 indexed citations
18.
Tang, Hui, et al.. (2009). Variation of meat quality traits among five genotypes of chicken. Poultry Science. 88(10). 2212–2218. 116 indexed citations
19.
Tang, Hui. (2009). Application of NAT Connection Between Configuration Hospital and Medicare Data Center. Chinese Medical Equipment Journal. 1 indexed citations
20.
Li, Biao, et al.. (2009). Identification of polymorphism of the callipyge mutation gene (CLPG) in goats and its associations with production traits.. Journal of Pharmaceutical and Biomedical Sciences. 17(2). 224–228. 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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