Qing Zhu

1.5k total citations
53 papers, 937 citations indexed

About

Qing Zhu is a scholar working on Animal Science and Zoology, Molecular Biology and Genetics. According to data from OpenAlex, Qing Zhu has authored 53 papers receiving a total of 937 indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Animal Science and Zoology, 18 papers in Molecular Biology and 14 papers in Genetics. Recurrent topics in Qing Zhu's work include Animal Nutrition and Physiology (22 papers), Livestock and Poultry Management (12 papers) and Cancer-related molecular mechanisms research (8 papers). Qing Zhu is often cited by papers focused on Animal Nutrition and Physiology (22 papers), Livestock and Poultry Management (12 papers) and Cancer-related molecular mechanisms research (8 papers). Qing Zhu collaborates with scholars based in China, United States and Switzerland. Qing Zhu's co-authors include Diyan Li, Xiaoling Zhao, Yiping Liu, Huadong Yin, Zhongxian Xu, Yiping Liu, Yan Wang, Hengyong Xu, Yong‐Gang Yao and Hang Zhong and has published in prestigious journals such as Nature Communications, PLoS ONE and Scientific Reports.

In The Last Decade

Qing Zhu

52 papers receiving 912 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Qing Zhu China 18 390 341 219 142 117 53 937
Yanyan Sun China 18 366 0.9× 285 0.8× 322 1.5× 175 1.2× 123 1.1× 98 995
Guobin Chang China 15 299 0.8× 279 0.8× 191 0.9× 126 0.9× 72 0.6× 110 726
Guohong Chen China 17 418 1.1× 404 1.2× 193 0.9× 129 0.9× 65 0.6× 101 869
Manman Shen China 19 375 1.0× 246 0.7× 339 1.5× 157 1.1× 117 1.0× 61 821
Songjia Lai China 19 329 0.8× 408 1.2× 336 1.5× 246 1.7× 79 0.7× 120 1.2k
Guiyun Xu China 22 790 2.0× 387 1.1× 555 2.5× 112 0.8× 158 1.4× 77 1.5k
Zhuocheng Hou China 21 516 1.3× 520 1.5× 573 2.6× 172 1.2× 210 1.8× 81 1.5k
Runshen Jiang China 16 545 1.4× 192 0.6× 237 1.1× 44 0.3× 92 0.8× 59 883
T. Wing United States 21 765 2.0× 221 0.6× 500 2.3× 82 0.6× 111 0.9× 30 1.3k
Yuanyuan Zhang China 16 152 0.4× 448 1.3× 206 0.9× 58 0.4× 157 1.3× 70 1.1k

Countries citing papers authored by Qing Zhu

Since Specialization
Citations

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

Fields of papers citing papers by Qing Zhu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Qing Zhu

This figure shows the co-authorship network connecting the top 25 collaborators of Qing Zhu. A scholar is included among the top collaborators of Qing Zhu 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 Qing Zhu. Qing Zhu 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.
Wang, Kaixin, Qing Zhu, Wen Liu, et al.. (2025). Mitochondrial apoptosis in response to cardiac ischemia-reperfusion injury. Journal of Translational Medicine. 23(1). 125–125. 2 indexed citations
2.
Meng, Xiaowei, Qianqian Wang, Fengmei Guo, et al.. (2025). Anti-inflammatory mechanisms of flavonoids in Pueraria lobata: Immune cell regulation and molecular mechanisms. Journal of Functional Foods. 131. 106954–106954.
3.
Li, Diyan, Chunyou Ning, Jiaman Zhang, et al.. (2022). Dynamic transcriptome and chromatin architecture in granulosa cells during chicken folliculogenesis. Nature Communications. 13(1). 131–131. 57 indexed citations
4.
Liu, Xueqin, Shailendra Kumar Mishra, Tao Wang, et al.. (2020). AFB1 Induced Transcriptional Regulation Related to Apoptosis and Lipid Metabolism in Liver of Chicken. Toxins. 12(5). 290–290. 53 indexed citations
5.
Ning, Chunyou, Silu Hu, Zhongxian Xu, et al.. (2020). Long Non-coding RNA and mRNA Profile of Liver Tissue During Four Developmental Stages in the Chicken. Frontiers in Genetics. 11. 574–574. 12 indexed citations
6.
Mishra, Shailendra Kumar, Binlong Chen, Qing Zhu, et al.. (2020). Transcriptome analysis reveals differentially expressed genes associated with high rates of egg production in chicken hypothalamic-pituitary-ovarian axis. Scientific Reports. 10(1). 5976–5976. 55 indexed citations
7.
Lan, Xi, Yan Wang, Kai Tian, et al.. (2017). Integrated host and viral transcriptome analyses reveal pathology and inflammatory response mechanisms to ALV-J injection in SPF chickens. Scientific Reports. 7(1). 46156–46156. 21 indexed citations
8.
Zhao, Xiaoling, P.B. Siegel, Juan Li, et al.. (2017). Meat quality characteristics of chickens as influenced by housing system, sex, and genetic line interactions. Italian Journal of Animal Science. 17(2). 462–468. 9 indexed citations
9.
Zhang, Long, Lu Lu, Siming Li, et al.. (2016). 1,25-Dihydroxyvitamin-D3 Induces Avian β-Defensin Gene Expression in Chickens. PLoS ONE. 11(5). e0154546–e0154546. 26 indexed citations
10.
Wu, Nan, Uma Gaur, Qing Zhu, et al.. (2016). Expressed microRNA associated with high rate of egg production in chicken ovarian follicles. Animal Genetics. 48(2). 205–216. 46 indexed citations
11.
Su, Yuan, Diyan Li, Uma Gaur, et al.. (2016). Genetic diversity of bitter taste receptor gene family in Sichuan domestic and Tibetan chicken populations. Journal of Genetics. 95(3). 675–681. 10 indexed citations
12.
Yin, Huadong, Rami A. Dalloul, Katarzyna B. Miska, et al.. (2015). Changes in expression of an antimicrobial peptide, digestive enzymes, and nutrient transporters in the intestine of E. praecox-infected chickens. Poultry Science. 94(7). 1521–1526. 13 indexed citations
13.
Liu, Lingbin, Diyan Li, Elizabeth R. Gilbert, et al.. (2015). Effect of Monochromatic Light on Expression of Estrogen Receptor (ER) and Progesterone Receptor (PR) in Ovarian Follicles of Chicken. PLoS ONE. 10(12). e0144102–e0144102. 30 indexed citations
14.
Li, Di, et al.. (2012). Genetic diversity and population structure in wild Sichuan rhesus macaques. Molecular Biology Reports. 40(4). 3033–3041. 3 indexed citations
15.
Yang, Jiandong, Zhihe Zhang, Fujun Shen, et al.. (2011). Microsatellite variability reveals high genetic diversity and low genetic differentiation in a critical giant panda population. Current Zoology. 57(6). 717–724. 7 indexed citations
16.
Zhang, K. Y., et al.. (2011). Influence of canthaxanthin on broiler breeder reproduction, chick quality, and performance. Poultry Science. 90(7). 1516–1522. 54 indexed citations
17.
Wang, Yan, Qing Zhu, Xiaoling Zhao, Yong‐Gang Yao, & Yiping Liu. (2010). Association of FATP1 gene polymorphisms with chicken carcass traits in Chinese meat-type quality chicken populations. Molecular Biology Reports. 37(8). 3683–3690. 10 indexed citations
18.
Zhu, Qing. (2009). Study on Association of Single Nucleotide Polymorphism of MEF2A Gene with Carcass Traits in Chicken. Xumu shouyi xuebao. 1 indexed citations
19.
Zhu, Qing. (2008). Effects of Progesterone on Progesterone Receptor Expression in Cultured Bovine Endometrial Cells (bEC). Xumu shouyi xuebao. 1 indexed citations
20.
Zhu, Qing, et al.. (2004). [The correlation analysis of microsatellite DNA markers for some production performances in chicken].. PubMed. 26(6). 854–8. 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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