Jiangjiang Zhu

715 total citations
32 papers, 526 citations indexed

About

Jiangjiang Zhu is a scholar working on Molecular Biology, Epidemiology and Physiology. According to data from OpenAlex, Jiangjiang Zhu has authored 32 papers receiving a total of 526 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Molecular Biology, 10 papers in Epidemiology and 10 papers in Physiology. Recurrent topics in Jiangjiang Zhu's work include Adipose Tissue and Metabolism (10 papers), Adipokines, Inflammation, and Metabolic Diseases (9 papers) and Lipid metabolism and biosynthesis (7 papers). Jiangjiang Zhu is often cited by papers focused on Adipose Tissue and Metabolism (10 papers), Adipokines, Inflammation, and Metabolic Diseases (9 papers) and Lipid metabolism and biosynthesis (7 papers). Jiangjiang Zhu collaborates with scholars based in China, United States and United Kingdom. Jiangjiang Zhu's co-authors include Hengbo Shi, Jun Luo, Yuting Sun, Juan J. Loor, G. Muralidharan, V. S. John Sunoj, Dawei Yao, Kun‐Fang Cao, Nabil I. Elsheery and Yaqiu Lin and has published in prestigious journals such as PLoS ONE, Journal of Dairy Science and BMC Genomics.

In The Last Decade

Jiangjiang Zhu

28 papers receiving 521 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jiangjiang Zhu China 12 220 169 107 96 88 32 526
M Galli Poland 8 243 1.1× 25 0.1× 76 0.7× 223 2.3× 56 0.6× 15 628
Huabin Zhu China 17 270 1.2× 63 0.4× 76 0.7× 30 0.3× 69 0.8× 33 905
Guobo Quan China 17 279 1.3× 99 0.6× 112 1.0× 54 0.6× 49 0.6× 57 788
David E. Cook United States 10 185 0.8× 41 0.2× 55 0.5× 31 0.3× 21 0.2× 26 494
Meng‐Hao Pan China 16 371 1.7× 77 0.5× 56 0.5× 46 0.5× 127 1.4× 57 837
Haoshu Luo China 14 277 1.3× 176 1.0× 61 0.6× 31 0.3× 140 1.6× 28 605
Borghild Tveit Norway 14 170 0.8× 82 0.5× 79 0.7× 20 0.2× 15 0.2× 23 541
Catherine S. Gardiner United States 13 288 1.3× 37 0.2× 82 0.8× 49 0.5× 32 0.4× 24 726
Yunwei Pang China 16 205 0.9× 33 0.2× 78 0.7× 44 0.5× 61 0.7× 38 792
Céline Zimmermann Switzerland 8 215 1.0× 101 0.6× 211 2.0× 64 0.7× 60 0.7× 8 665

Countries citing papers authored by Jiangjiang Zhu

Since Specialization
Citations

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

Fields of papers citing papers by Jiangjiang Zhu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jiangjiang Zhu

This figure shows the co-authorship network connecting the top 25 collaborators of Jiangjiang Zhu. A scholar is included among the top collaborators of Jiangjiang 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 Jiangjiang Zhu. Jiangjiang 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.
Zhang, Xinnan, Yao Wang, Jie Liu, et al.. (2025). Mannose-modified erythrocyte membrane-coated Chuanmingshen violaceum polysaccharide PLGA nanoparticles to improve immune responses in mice. International Immunopharmacology. 152. 114450–114450. 2 indexed citations
2.
Xiang, Hua, et al.. (2025). C1QBP promotes apoptosis of goat fetal turbinate cells via inhibiting the expression of TRIM5 or TNFSF10. Frontiers in Veterinary Science. 12. 1524734–1524734. 1 indexed citations
3.
Li, Haiyang, Zi‐jun Xu, Yaqiu Lin, et al.. (2025). Global profiling of protein lysine Malonylation during goat intramuscular Preadipocyte differentiation. Journal of Proteomics. 321. 105521–105521.
4.
Huang, Zhiqing, Changhui Zhang, Lian Huang, et al.. (2025). CIDEB promotes lipid deposition in goat intramuscular adipocytes. Animal Bioscience. 38(5). 884–897.
5.
Li, Qi, Yaqiu Lin, Yong Wang, et al.. (2023). MCD Inhibits Lipid Deposition in Goat Intramuscular Preadipocytes. Genes. 14(2). 440–440. 8 indexed citations
6.
Zhang, Huanrong, Yupeng Ren, Honghong He, et al.. (2023). The orf virus 129 protein can inhibit immune responses by interacting with host complement C1q binding protein in goat turbinate bone cells. Veterinary Microbiology. 283. 109782–109782. 2 indexed citations
7.
8.
Xie, Jingwen, et al.. (2022). Fatty acid profiles in Chinese Maiwa yak milk across the lactation cycle. AFRICAN JOURNAL OF BIOTECHNOLOGY. 21(7). 314–323.
9.
Zhang, Hao, Yong Wang, Yanyan Li, et al.. (2022). Overexpression of goat STEAP4 promotes the differentiation of subcutaneous adipocytes. Archives animal breeding/Archiv für Tierzucht. 65(4). 397–406. 2 indexed citations
10.
11.
Elsheery, Nabil I., et al.. (2020). Foliar application of nanoparticles mitigates the chilling effect on photosynthesis and photoprotection in sugarcane. Plant Physiology and Biochemistry. 149. 50–60. 111 indexed citations
12.
Wang, Hui, Jiangjiang Zhu, Qiuya He, Juan J. Loor, & Jun Luo. (2018). Association between the expression of miR‐26 and goat milk fatty acids. Reproduction in Domestic Animals. 53(6). 1478–1482. 15 indexed citations
13.
Lin, Yaqiu, Jiangjiang Zhu, Yong Wang, Qian Li, & Sen Lin. (2017). Identification of differentially expressed genes through RNA sequencing in goats (Capra hircus) at different postnatal stages. PLoS ONE. 12(8). e0182602–e0182602. 27 indexed citations
14.
Shi, Hengbo, Min Wu, Jiangjiang Zhu, et al.. (2017). Fatty acid elongase 6 plays a role in the synthesis of long-chain fatty acids in goat mammary epithelial cells. Journal of Dairy Science. 100(6). 4987–4995. 46 indexed citations
15.
Chen, Zhi, Jun Luo, Hui Wang, et al.. (2015). MiR130b-Regulation of PPARγ Coactivator- 1α Suppresses Fat Metabolism in Goat Mammary Epithelial Cells. PLoS ONE. 10(11). e0142809–e0142809. 35 indexed citations
16.
Wang, Haihua, Jun Luo, Wenting Cao, et al.. (2015). MicroRNA-24 can control triacylglycerol synthesis in goat mammary epithelial cells by targeting the fatty acid synthase gene. Journal of Dairy Science. 98(12). 9001–9014. 35 indexed citations
17.
Shi, Hengbo, Kang Yu, Jun Luo, et al.. (2015). Adipocyte differentiation-related protein promotes lipid accumulation in goat mammary epithelial cells. Journal of Dairy Science. 98(10). 6954–6964. 20 indexed citations
18.
Li, Jun, Jun Luo, Jiangjiang Zhu, et al.. (2015). Regulation of the fatty acid synthase promoter by liver X receptor α through direct and indirect mechanisms in goat mammary epithelial cells. Comparative Biochemistry and Physiology Part B Biochemistry and Molecular Biology. 184. 44–51. 19 indexed citations
19.
Shi, Hengbo, Jiangjiang Zhu, Jun Luo, et al.. (2014). Genes regulating lipid and protein metabolism are highly expressed in mammary gland of lactating dairy goats. Functional & Integrative Genomics. 15(3). 309–321. 53 indexed citations
20.
Zhu, Jiangjiang, Jun Luo, Kang Yu, et al.. (2014). Inhibition of FASN reduces the synthesis of medium-chain fatty acids in goat mammary gland. animal. 8(9). 1469–1478. 59 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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