Yingli Jia

999 total citations
26 papers, 743 citations indexed

About

Yingli Jia is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience and Endocrinology, Diabetes and Metabolism. According to data from OpenAlex, Yingli Jia has authored 26 papers receiving a total of 743 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Molecular Biology, 5 papers in Cellular and Molecular Neuroscience and 5 papers in Endocrinology, Diabetes and Metabolism. Recurrent topics in Yingli Jia's work include Receptor Mechanisms and Signaling (5 papers), Neuropeptides and Animal Physiology (4 papers) and Renal and related cancers (3 papers). Yingli Jia is often cited by papers focused on Receptor Mechanisms and Signaling (5 papers), Neuropeptides and Animal Physiology (4 papers) and Renal and related cancers (3 papers). Yingli Jia collaborates with scholars based in China, United States and Romania. Yingli Jia's co-authors include Baoxue Yang, Xiaoqiang Geng, Lei Lei, Hong Zhou, Jinzhao He, Min Li, Ang Ma, Jianhua Ran, Dandan Zhong and Liang Wang and has published in prestigious journals such as Nature Communications, Blood and Analytical Chemistry.

In The Last Decade

Yingli Jia

22 papers receiving 737 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Yingli Jia China 15 371 142 104 76 66 26 743
Yunzhuo Ren China 20 536 1.4× 264 1.9× 94 0.9× 74 1.0× 119 1.8× 30 1.0k
Chang Joo Oh South Korea 14 419 1.1× 96 0.7× 58 0.6× 60 0.8× 101 1.5× 26 802
Haijiang Wu China 18 612 1.6× 220 1.5× 114 1.1× 95 1.3× 114 1.7× 27 1.1k
Sara Di Silvestre Italy 19 287 0.8× 73 0.5× 123 1.2× 122 1.6× 96 1.5× 30 902
Zhonggao Xu China 12 722 1.9× 218 1.5× 91 0.9× 68 0.9× 120 1.8× 18 1.2k
Bridget Ford United States 11 410 1.1× 130 0.9× 72 0.7× 36 0.5× 89 1.3× 15 728
Chi Young Song United States 20 280 0.8× 171 1.2× 85 0.8× 55 0.7× 85 1.3× 37 810
Dilinaer Bolati Japan 9 284 0.8× 384 2.7× 70 0.7× 62 0.8× 62 0.9× 10 760
Xinzhong Huang China 14 409 1.1× 175 1.2× 80 0.8× 65 0.9× 69 1.0× 40 1.0k
Rubina Novelli Italy 17 451 1.2× 330 2.3× 125 1.2× 90 1.2× 119 1.8× 36 1.0k

Countries citing papers authored by Yingli Jia

Since Specialization
Citations

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

Fields of papers citing papers by Yingli Jia

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yingli Jia

This figure shows the co-authorship network connecting the top 25 collaborators of Yingli Jia. A scholar is included among the top collaborators of Yingli Jia 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 Yingli Jia. Yingli Jia 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, Yingchen, et al.. (2025). High-Sensitivity Measurement of Crystallization Induction Period Based on Fluorescence Method. Crystal Growth & Design. 25(15). 6000–6013.
2.
Zhang, Hongdan, Jianwei Liu, Yingli Jia, et al.. (2025). LncPrep + 96kb inhibits ovarian fibrosis by upregulating prolyl oligopeptidase expression. Molecular Medicine Reports. 31(5). 1–11.
3.
4.
Jia, Yingli, et al.. (2023). Lipin-1 deficiency deteriorates defect of fatty acid β-oxidation and lipid-related kidney damage in diabetic kidney disease. Translational research. 266. 1–15. 12 indexed citations
5.
Du, Yaqin, Jie Cheng, Jing‐Yu Lin, et al.. (2022). Endogenous Lipid-GPR120 Signaling Modulates Pancreatic Islet Homeostasis to Different Extents. Diabetes. 71(7). 1454–1471. 20 indexed citations
6.
Jia, Yingli, Ang Ma, Jinzhao He, et al.. (2022). Dapagliflozin protects against nonalcoholic steatohepatitis in db/db mice. Frontiers in Pharmacology. 13. 934136–934136. 12 indexed citations
7.
He, Qing‐tao, Peng Xiao, Shen-Ming Huang, et al.. (2021). Structural studies of phosphorylation-dependent interactions between the V2R receptor and arrestin-2. Nature Communications. 12(1). 2396–2396. 50 indexed citations
8.
Zhao, Shuai, Shengchao Guo, Chan Yang, et al.. (2020). Cell active and functionally-relevant small-molecule agonists of calcitonin receptor. Bioorganic Chemistry. 96. 103596–103596. 3 indexed citations
9.
Zhang, Daolai, Yanfei Wang, Hui Lin, et al.. (2020). Function and therapeutic potential of G protein‐coupled receptors in epididymis. British Journal of Pharmacology. 177(24). 5489–5508. 15 indexed citations
10.
Geng, Xiaoqiang, Ang Ma, Jinzhao He, et al.. (2019). Ganoderic acid hinders renal fibrosis via suppressing the TGF-β/Smad and MAPK signaling pathways. Acta Pharmacologica Sinica. 41(5). 670–677. 147 indexed citations
11.
He, Jinzhao, Yi Sun, Yingli Jia, et al.. (2019). Ganoderma triterpenes Protect Against Hyperhomocysteinemia Induced Endothelial-Mesenchymal Transition via TGF-β Signaling Inhibition. Frontiers in Physiology. 10. 192–192. 17 indexed citations
12.
Wang, Weiling, Xiaoqiang Geng, Lei Lei, et al.. (2019). Aquaporin‐3 deficiency slows cyst enlargement in experimental mouse models of autosomal dominant polycystic kidney disease. The FASEB Journal. 33(5). 6185–6196. 15 indexed citations
13.
Jia, Yingli, Jinzhao He, Liang Wang, et al.. (2018). Dapagliflozin Aggravates Renal Injury via Promoting Gluconeogenesis in db/db Mice. Cellular Physiology and Biochemistry. 45(5). 1747–1758. 36 indexed citations
14.
Liu, Liying, Yingli Jia, Lei Lei, et al.. (2017). Ganoderma triterpenes retard renal cyst development by downregulating Ras/MAPK signaling and promoting cell differentiation. Kidney International. 92(6). 1404–1418. 29 indexed citations
15.
Lei, Lei, Weiling Wang, Yingli Jia, et al.. (2017). Aquaporin-3 deletion in mice results in renal collecting duct abnormalities and worsens ischemia-reperfusion injury. Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease. 1863(6). 1231–1241. 25 indexed citations
16.
17.
Jia, Yingli, Yi Sun, Lin Weng, et al.. (2016). Low molecular weight fucoidan protects renal tubular cells from injury induced by albumin overload. Scientific Reports. 6(1). 31759–31759. 25 indexed citations
18.
Li, Yingjie, et al.. (2015). Propofol Prevents Renal Ischemia-Reperfusion Injury via Inhibiting the Oxidative Stress Pathways. Cellular Physiology and Biochemistry. 37(1). 14–26. 60 indexed citations
19.
Huang, Yaqian, Dingfang Bu, Lars Holmberg, et al.. (2014). Sulfur dioxide inhibits vascular smooth muscle cell proliferation via suppressing the Erk/MAP kinase pathway mediated by cAMP/PKA signaling. Cell Death and Disease. 5(5). e1251–e1251. 104 indexed citations
20.
Wei, Yue, Sophie Dimicoli, Carlos E. Bueso‐Ramos, et al.. (2013). Global H3K4me3 genome mapping reveals alterations of innate immunity signaling and overexpression of JMJD3 in human myelodysplastic syndrome CD34+ cells. Leukemia. 27(11). 2177–2186. 66 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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