Huanmin Zhang

2.6k total citations
113 papers, 2.0k citations indexed

About

Huanmin Zhang is a scholar working on Epidemiology, Molecular Biology and Immunology. According to data from OpenAlex, Huanmin Zhang has authored 113 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 56 papers in Epidemiology, 55 papers in Molecular Biology and 33 papers in Immunology. Recurrent topics in Huanmin Zhang's work include Herpesvirus Infections and Treatments (46 papers), Cytomegalovirus and herpesvirus research (27 papers) and interferon and immune responses (20 papers). Huanmin Zhang is often cited by papers focused on Herpesvirus Infections and Treatments (46 papers), Cytomegalovirus and herpesvirus research (27 papers) and interferon and immune responses (20 papers). Huanmin Zhang collaborates with scholars based in United States, China and Egypt. Huanmin Zhang's co-authors include Jiuzhou Song, Qingmei Xie, Fei Tian, Mohammad Heidari, Shuang Chang, Xinheng Zhang, Juan Luo, Wencheng Lin, Hongxin Li and Shuang Chang and has published in prestigious journals such as Proceedings of the National Academy of Sciences, PLoS ONE and Journal of Virology.

In The Last Decade

Huanmin Zhang

105 papers receiving 1.9k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Huanmin Zhang United States 27 821 590 495 419 384 113 2.0k
Stephen N. White United States 26 500 0.6× 430 0.7× 581 1.2× 897 2.1× 210 0.5× 99 2.4k
R. S. Kataria India 23 422 0.5× 415 0.7× 492 1.0× 668 1.6× 154 0.4× 206 1.7k
Jun Luo China 22 729 0.9× 482 0.8× 137 0.3× 188 0.4× 181 0.5× 108 1.5k
Dewen Tong China 26 598 0.7× 215 0.4× 684 1.4× 490 1.2× 315 0.8× 103 1.8k
Hirohide Uenishi Japan 24 488 0.6× 147 0.2× 337 0.7× 501 1.2× 766 2.0× 131 1.9k
Li Gao China 29 660 0.8× 1.3k 2.2× 892 1.8× 603 1.4× 501 1.3× 169 2.9k
Paul M. Coussens United States 38 1.5k 1.8× 1.6k 2.7× 373 0.8× 771 1.8× 690 1.8× 105 4.0k
Min Feng China 22 700 0.9× 247 0.4× 207 0.4× 104 0.2× 467 1.2× 85 1.4k
Yaofeng Zhao China 31 1.2k 1.5× 184 0.3× 179 0.4× 440 1.1× 1.3k 3.3× 123 2.8k
Yingli Shang China 21 530 0.6× 350 0.6× 204 0.4× 189 0.5× 626 1.6× 49 1.4k

Countries citing papers authored by Huanmin Zhang

Since Specialization
Citations

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

Fields of papers citing papers by Huanmin Zhang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Huanmin Zhang

This figure shows the co-authorship network connecting the top 25 collaborators of Huanmin Zhang. A scholar is included among the top collaborators of Huanmin Zhang 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 Huanmin Zhang. Huanmin Zhang 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.
Yu, Xudong, et al.. (2025). A peptide-based fluorescent bioprobe for EphA2-overexpressing tumor targeting and image-guided surgical resection. Bioorganic & Medicinal Chemistry. 120. 118090–118090.
2.
Kuang, Zhenzhong, Sheng Chen, Xuefeng Zhu, et al.. (2025). Insertion/deletion mutations within tva receptor gene confer chicken resistance to infection by avian leukosis virus subgroups A and K. Poultry Science. 104(4). 104949–104949.
3.
4.
Hu, Jiaying, et al.. (2024). The Impact of Early-Life Cecal Microbiota Transplantation on Social Stress and Injurious Behaviors in Egg-Laying Chickens. Microorganisms. 12(3). 471–471. 7 indexed citations
5.
6.
Heidari, Mohammad, Huanmin Zhang, Lakshmi T. Sunkara, & Syed Mudasir Ahmad. (2023). Role of T Cells in Vaccine-Mediated Immunity against Marek’s Disease. Viruses. 15(3). 648–648. 4 indexed citations
7.
Hu, Jiaying, Timothy A. Johnson, Huanmin Zhang, & H.W. Cheng. (2022). The Microbiota–Gut–Brain Axis: Gut Microbiota Modulates Conspecific Aggression in Diversely Selected Laying Hens. Microorganisms. 10(6). 1081–1081. 20 indexed citations
8.
Pu, Yong, et al.. (2022). Sex-specific extracellular matrix remodeling during early adipogenic differentiation by gestational bisphenol A exposure. Chemosphere. 302. 134806–134806. 3 indexed citations
9.
Chen, Weiguo, Xiangyu Zhang, Xiangyu Zhang, et al.. (2022). Semen extracellular vesicles mediate vertical transmission of subgroup J avian leukosis virus. Virologica Sinica. 37(2). 284–294. 11 indexed citations
10.
Zhang, Xinheng, Qiqi Zhao, Sheng Chen, et al.. (2020). Effect of Baicalin on Bacterial Secondary Infection and Inflammation Caused by H9N2 AIV Infection in Chickens. BioMed Research International. 2020(1). 14 indexed citations
11.
Li, Haijuan, Peikun Wang, Lulu Lin, et al.. (2018). The emergence of the infection of subgroup J avian leucosis virus escalated the tumour incidence in commercial Yellow chickens in Southern China in recent years. Transboundary and Emerging Diseases. 66(1). 312–316. 45 indexed citations
12.
Xu, Lingyang, Yanghua He, Yi Ding, et al.. (2018). Genetic assessment of inbred chicken lines indicates genomic signatures of resistance to Marek’s disease. Journal of Animal Science and Biotechnology. 9(1). 65–65. 12 indexed citations
13.
Xu, Lingyang, Yanghua He, Yi Ding, et al.. (2017). Characterization of Copy Number Variation’s Potential Role in Marek’s Disease. International Journal of Molecular Sciences. 18(5). 1020–1020. 9 indexed citations
14.
15.
Sun, Aijun, Lucy F. Lee, Owais Khan, et al.. (2013). Deletion of Marek's Disease Virus Large Subunit of Ribonucleotide Reductase Impairs Virus Growth In Vitro and In Vivo. Avian Diseases. 57(2s1). 464–468. 9 indexed citations
16.
Xu, Ming, Scott D. Fitzgerald, Huanmin Zhang, D.M. Karcher, & Mohammad Heidari. (2012). Very Virulent Plus Strains of MDV Induce an Acute Form of Transient Paralysis in Both Susceptible and Resistant Chicken Lines. Viral Immunology. 25(4). 306–323. 11 indexed citations
17.
Luo, Juan, Yingyan Yu, Shuang Chang, et al.. (2012). DNA Methylation Fluctuation Induced by Virus Infection Differs between MD-resistant and -susceptible Chickens. Frontiers in Genetics. 3. 20–20. 28 indexed citations
18.
Luo, Juan, Yingyan Yu, Huanmin Zhang, et al.. (2011). Down-regulation of promoter methylation level of CD4 gene after MDV infection in MD-susceptible chicken line. BMC Proceedings. 5(S4). S7–S7. 29 indexed citations
19.
Tian, Fei, Juan Luo, Huanmin Zhang, Shuang Chang, & Jiuzhou Song. (2011). MiRNA expression signatures induced by Marek's disease virus infection in chickens. Genomics. 99(3). 152–159. 57 indexed citations
20.
Zhang, Huanmin, Henry D. Hunt, Hans H. Cheng, et al.. (2005). Identification and evaluation of SNPs at the 3’ end of the tva gene segregating among ALSV resistance and susceptible lines of chickens. Kent Academic Repository (University of Kent). 2 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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