Ming Sang

2.0k total citations
79 papers, 1.4k citations indexed

About

Ming Sang is a scholar working on Molecular Biology, Immunology and Cancer Research. According to data from OpenAlex, Ming Sang has authored 79 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 40 papers in Molecular Biology, 17 papers in Immunology and 9 papers in Cancer Research. Recurrent topics in Ming Sang's work include Neurobiology and Insect Physiology Research (7 papers), Insect Resistance and Genetics (7 papers) and Immune Response and Inflammation (6 papers). Ming Sang is often cited by papers focused on Neurobiology and Insect Physiology Research (7 papers), Insect Resistance and Genetics (7 papers) and Immune Response and Inflammation (6 papers). Ming Sang collaborates with scholars based in China, United States and South Korea. Ming Sang's co-authors include Chengjun Li, Wei Wu, Bin Li, Xiaodong Sun, Lixia Xie, Yuanming Zhang, Yujun Tao, Yi Zhu, Chengwu Zhang and Tao Li and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Analytical Biochemistry.

In The Last Decade

Ming Sang

76 papers receiving 1.4k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ming Sang China 22 685 215 173 153 137 79 1.4k
Mirna Marques Bezerra Brazil 24 470 0.7× 146 0.7× 147 0.8× 28 0.2× 286 2.1× 83 1.8k
Saori Kobayashi Japan 22 927 1.4× 121 0.6× 83 0.5× 25 0.2× 103 0.8× 57 2.0k
Yu Chen China 34 1.4k 2.0× 551 2.6× 131 0.8× 71 0.5× 532 3.9× 159 3.0k
Kiminori Matsubara Japan 26 1.1k 1.5× 119 0.6× 43 0.2× 44 0.3× 298 2.2× 75 2.4k
Qingrong Li China 23 730 1.1× 202 0.9× 126 0.7× 218 1.4× 152 1.1× 97 1.6k
Xiuqi Wang China 29 909 1.3× 97 0.5× 69 0.4× 48 0.3× 275 2.0× 137 2.2k
Ting‐Jun Fan China 21 990 1.4× 472 2.2× 138 0.8× 64 0.4× 144 1.1× 94 2.3k
Jiajia Song China 26 1.1k 1.6× 106 0.5× 62 0.4× 165 1.1× 162 1.2× 131 2.1k
Arianna Mastrofrancesco Italy 26 487 0.7× 198 0.9× 21 0.1× 67 0.4× 47 0.3× 42 1.9k
Jung‐Bum Lee Japan 32 666 1.0× 272 1.3× 89 0.5× 24 0.2× 657 4.8× 94 3.0k

Countries citing papers authored by Ming Sang

Since Specialization
Citations

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

Fields of papers citing papers by Ming Sang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ming Sang

This figure shows the co-authorship network connecting the top 25 collaborators of Ming Sang. A scholar is included among the top collaborators of Ming Sang 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 Ming Sang. Ming Sang 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.
Sun, Xiaodong, et al.. (2025). Withaferin A maintained microbiome and metabolome features in A53T transgenic mice via multi-omics integrated analysis. Phytomedicine. 141. 156725–156725. 2 indexed citations
2.
Xu, Jian‐Guang, et al.. (2025). Nav1.6 drives colorectal cancer proliferation and invasion through MAPK signaling pathway. World Journal of Gastrointestinal Oncology. 17(7). 105264–105264. 1 indexed citations
3.
Sang, Ming, W. Xu, Yonggen Chen, et al.. (2024). Processed Buthus martensii Karsch scorpions ameliorate diet-induced NASH in mice by attenuating Kv1.3-mediated macrophage activation. Journal of Ethnopharmacology. 337(Pt 1). 118794–118794. 1 indexed citations
4.
Lee, Myeong Hwan, Eunjeong Kang, Yong Chul Kim, et al.. (2024). Silent gallbladder stone in kidney transplantation recipients: should it be treated? A retrospective cohort study. International Journal of Surgery. 110(6). 3571–3579.
5.
Wang, Zhiheng, Ming Sang, Yuxin Zhang, et al.. (2023). BmKK2, a thermostable Kv1.3 blocker from Buthus martensii Karsch (BmK) scorpion, inhibits the activation of macrophages via Kv1.3-NF-κB- NLRP3 axis. Journal of Ethnopharmacology. 314. 116624–116624. 13 indexed citations
6.
Zeng, Lian, Zhen Zhang, Min Xu, et al.. (2021). P53 inhibitor pifithrin‐α inhibits ropivacaine‐induced neuronal apoptosis via the mitochondrial apoptosis pathway. Journal of Biochemical and Molecular Toxicology. 35(8). e22822–e22822. 7 indexed citations
7.
Ma, Ming, et al.. (2020). Knockdown of FAM83D Enhances Radiosensitivity in Coordination with Irradiation by Inhibiting EMT via the Akt/GSK-3β/Snail Signaling Pathway in Human Esophageal Cancer Cells. SHILAP Revista de lepidopterología. 2 indexed citations
8.
Liu, Yue, et al.. (2019). SS31 Ameliorates Sepsis-Induced Heart Injury by Inhibiting Oxidative Stress and Inflammation. Inflammation. 42(6). 2170–2180. 51 indexed citations
9.
Liu, Xiaozhen, Xiaoping Liu, Zhiming Zhang, et al.. (2018). Functional Analysis of the FZF1 Genes of Saccharomyces uvarum. Frontiers in Microbiology. 9. 96–96. 11 indexed citations
10.
Ma, Tongcui, Runhong Zhou, Xu Wang, et al.. (2016). Soybean-derived Bowman-Birk Inhibitor (BBI) Inhibits HIV Replication in Macrophages. Scientific Reports. 6(1). 34752–34752. 10 indexed citations
11.
Wang, Jing, et al.. (2016). MicroRNA-205-5b inhibits HMGB1 expression in LPS-induced sepsis. International Journal of Molecular Medicine. 38(1). 312–318. 42 indexed citations
12.
Sang, Ming, Jiaxin Zhang, Bin Li, & Yuqing Chen. (2016). TRAIL-CM4 fusion protein shows in vitro antibacterial activity and a stronger antitumor activity than solo TRAIL protein. Protein Expression and Purification. 122. 82–89. 7 indexed citations
13.
Zhou, Li, Jieliang Li, Yu Zhou, et al.. (2015). Induction of interferon-λ contributes to TLR3 and RIG-I activation-mediated inhibition of herpes simplex virus type 2 replication in human cervical epithelial cells. Molecular Human Reproduction. 21(12). 917–929. 24 indexed citations
15.
Li, Chengjun, Xiaowen Song, Xuhong Chen, et al.. (2014). Identification and comparative analysis of G protein-coupled receptors in Pediculus humanus humanus. Genomics. 104(1). 58–67. 9 indexed citations
16.
Sang, Ming, et al.. (2014). Ischaemic Heart Disease at the University Hospital of the West Indies: Trends in Hospital Admissions and Inpatient Mortality Rates 2005−2010. West Indian Medical Journal. 63(5). 424–30. 1 indexed citations
17.
Zhang, Yi, et al.. (2013). Identification and characterization of novel ER-based hsp90 gene in the red flour beetle, Tribolium castaneum. Cell Stress and Chaperones. 19(5). 623–633. 20 indexed citations
18.
Li, Chengjun, Yi Zhang, Ming Sang, et al.. (2013). Identification of G protein-coupled receptors in the pea aphid, Acyrthosiphon pisum. Genomics. 102(4). 345–354. 40 indexed citations
19.
Zhang, Jiaxin, Ming Sang, Wei Zhao, et al.. (2011). Molecular structure and characterization of the cytokine TWEAK and its receptor Fn14 in bovine. Veterinary Immunology and Immunopathology. 144(3-4). 238–246. 6 indexed citations
20.
Cui, Min, et al.. (2010). A cationic amphiphilic peptide ABP-CM4 exhibits selective cytotoxicity against leukemia cells. Peptides. 31(8). 1504–1510. 43 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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