Ping Kang

1.4k total citations
31 papers, 1.1k citations indexed

About

Ping Kang is a scholar working on Molecular Biology, Aging and Immunology. According to data from OpenAlex, Ping Kang has authored 31 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Molecular Biology, 8 papers in Aging and 8 papers in Immunology. Recurrent topics in Ping Kang's work include Genetics, Aging, and Longevity in Model Organisms (8 papers), Neurobiology and Insect Physiology Research (6 papers) and Invertebrate Immune Response Mechanisms (3 papers). Ping Kang is often cited by papers focused on Genetics, Aging, and Longevity in Model Organisms (8 papers), Neurobiology and Insect Physiology Research (6 papers) and Invertebrate Immune Response Mechanisms (3 papers). Ping Kang collaborates with scholars based in China, United States and Canada. Ping Kang's co-authors include Hua Bai, Marc Tatar, Ying Zhong, Kartik Shankar, Yulong Yin, Michael L. Blackburn, Sarah J. Borengasser, Thomas M. Badger, Chang Zhao and Jin‐Ran Chen and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Communications and PLoS ONE.

In The Last Decade

Ping Kang

31 papers receiving 1.0k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ping Kang China 17 361 246 231 180 140 31 1.1k
Maroun Bou Sleiman Switzerland 17 453 1.3× 65 0.3× 130 0.6× 124 0.7× 169 1.2× 30 945
Deying Yang China 17 537 1.5× 62 0.3× 130 0.6× 97 0.5× 153 1.1× 66 1.1k
Yhong‐Hee Shim South Korea 22 1.1k 3.0× 33 0.1× 676 2.9× 56 0.3× 129 0.9× 78 1.7k
Hyung‐Lyun Kang South Korea 14 530 1.5× 87 0.4× 112 0.5× 221 1.2× 74 0.5× 53 1.2k
Marı́a J. Bragado Spain 24 620 1.7× 133 0.5× 17 0.1× 89 0.5× 83 0.6× 69 1.6k
Emma Thomas Australia 7 562 1.6× 42 0.2× 489 2.1× 297 1.6× 279 2.0× 9 1.4k
Takehito Kuwayama Japan 29 797 2.2× 31 0.1× 155 0.7× 285 1.6× 207 1.5× 125 2.5k
Ciara M Gallagher United States 9 1.0k 2.9× 134 0.5× 51 0.2× 145 0.8× 165 1.2× 13 1.9k
Tim Y. Hou United States 15 361 1.0× 89 0.4× 19 0.1× 314 1.7× 105 0.8× 21 918
Orane Visvikis France 14 962 2.7× 44 0.2× 435 1.9× 209 1.2× 278 2.0× 20 1.9k

Countries citing papers authored by Ping Kang

Since Specialization
Citations

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

Fields of papers citing papers by Ping Kang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ping Kang

This figure shows the co-authorship network connecting the top 25 collaborators of Ping Kang. A scholar is included among the top collaborators of Ping Kang 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 Ping Kang. Ping Kang 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, Xinyu, Ping Kang, Jinshuai Lan, et al.. (2025). Exploring the influence of polysaccharide on gastrointestinal stability, drug release and formation mechanism of nanoparticles in Zhimu and Huangbai herb pair decoction. Scientific Reports. 15(1). 8293–8293. 1 indexed citations
2.
Lan, Chunyan, Xiayan Liu, Yan Wang, et al.. (2023). CA916798 predicts poor prognosis and promotes Gefitinib resistance for lung adenocarcinoma. BMC Cancer. 23(1). 266–266. 1 indexed citations
3.
Dai, Dao‐Fu, Ping Kang, & Hua Bai. (2023). The mTOR signaling pathway in cardiac aging. PubMed. 3(3). 12 indexed citations
4.
Miao, Ting, et al.. (2022). Acetyl-CoA-mediated autoacetylation of fatty acid synthase as a metabolic switch of de novo lipogenesis in Drosophila. Proceedings of the National Academy of Sciences. 119(49). e2212220119–e2212220119. 8 indexed citations
5.
Chang, Kai, et al.. (2021). FOXO Regulates Neuromuscular Junction Homeostasis During Drosophila Aging. Frontiers in Aging Neuroscience. 12. 567861–567861. 11 indexed citations
6.
Qu, Linlin, et al.. (2021). Use of nimotuzumab combined with cisplatin in treatment of nasopharyngeal carcinoma and its effect on expressions of VEGF and MMP-2. Clinical & Translational Oncology. 23(7). 1342–1349. 5 indexed citations
7.
Zhang, Yushan, et al.. (2021). Halofuginone Sensitizes Lung Cancer Organoids to Cisplatin via Suppressing PI3K/AKT and MAPK Signaling Pathways. Frontiers in Cell and Developmental Biology. 9. 773048–773048. 27 indexed citations
8.
Huang, Kerui, Ting Miao, Kai Chang, et al.. (2020). Impaired peroxisomal import in Drosophila oenocytes causes cardiac dysfunction by inducing upd3 as a peroxikine. Nature Communications. 11(1). 2943–2943. 28 indexed citations
9.
Zheng, Tingting, Liyang Dong, Chaoming Mao, et al.. (2019). Caveolin-1 Regulates CCL5 and PPARγ Expression in Nthy-ori 3-1 Cells: Possible Involvement of Caveolin-1 and CCL5 in the Pathogenesis of Hashimoto’s Thyroiditis. Endocrine Metabolic & Immune Disorders - Drug Targets. 20(4). 609–618. 2 indexed citations
10.
Huang, Kerui, et al.. (2019). Organelle aging: Lessons from model organisms. Journal of genetics and genomics. 46(4). 171–185. 18 indexed citations
11.
Liu, Jiameng, Chaoming Mao, Liyang Dong, et al.. (2019). Excessive Iodine Promotes Pyroptosis of Thyroid Follicular Epithelial Cells in Hashimoto's Thyroiditis Through the ROS-NF-κB-NLRP3 Pathway. Frontiers in Endocrinology. 10. 778–778. 38 indexed citations
12.
Zheng, Wenjing, Florentina Rus, Ana Hernández, et al.. (2018). Dehydration triggers ecdysone-mediated recognition-protein priming and elevated anti-bacterial immune responses in Drosophila Malpighian tubule renal cells. BMC Biology. 16(1). 60–60. 33 indexed citations
13.
Wankhade, Umesh D., Ying Zhong, Ping Kang, et al.. (2018). Maternal High-Fat Diet Programs Offspring Liver Steatosis in a Sexually Dimorphic Manner in Association with Changes in Gut Microbial Ecology in Mice. Scientific Reports. 8(1). 16502–16502. 78 indexed citations
14.
Zhang, Xiaotian, Yue Ding, Ping Kang, Xinyu Zhang, & Tong Zhang. (2018). Forsythoside A Modulates Zymosan-Induced Peritonitis in Mice. Molecules. 23(3). 593–593. 27 indexed citations
15.
Kang, Ping, Kai Chang, Ying Liu, et al.. (2017). Drosophila Kruppel homolog 1 represses lipolysis through interaction with dFOXO. Scientific Reports. 7(1). 16369–16369. 47 indexed citations
16.
Bai, Hua, Stephanie Post, Ping Kang, & Marc Tatar. (2015). Drosophila Longevity Assurance Conferred by Reduced Insulin Receptor Substrate Chico Partially Requires d4eBP. PLoS ONE. 10(8). e0134415–e0134415. 21 indexed citations
17.
Bai, Hua, et al.. (2013). Activin Signaling Targeted by Insulin/dFOXO Regulates Aging and Muscle Proteostasis in Drosophila. PLoS Genetics. 9(11). e1003941–e1003941. 160 indexed citations
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20.
Kang, Ping, et al.. (2010). Epidermal Growth Factor-Expressing Lactococcus lactis Enhances Intestinal Development of Early-Weaned Pigs. Journal of Nutrition. 140(4). 806–811. 44 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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