Ming Lu

2.3k total citations
62 papers, 1.8k citations indexed

About

Ming Lu is a scholar working on Molecular Biology, Epidemiology and Oncology. According to data from OpenAlex, Ming Lu has authored 62 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 35 papers in Molecular Biology, 14 papers in Epidemiology and 12 papers in Oncology. Recurrent topics in Ming Lu's work include Antibiotic Resistance in Bacteria (11 papers), Pancreatitis Pathology and Treatment (6 papers) and Enterobacteriaceae and Cronobacter Research (5 papers). Ming Lu is often cited by papers focused on Antibiotic Resistance in Bacteria (11 papers), Pancreatitis Pathology and Treatment (6 papers) and Enterobacteriaceae and Cronobacter Research (5 papers). Ming Lu collaborates with scholars based in China, United States and Sweden. Ming Lu's co-authors include Qinghua Cui, Chengxiang Qiu, Juan Wang, Lee F. Kolakowski, Edward W. McBride, Laurence J. Miller, Martin Beinborn, Herbert Y. Lin, Xin Qiao and Wei Zhao and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and SHILAP Revista de lepidopterología.

In The Last Decade

Ming Lu

55 papers receiving 1.8k 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 Lu China 19 1.0k 482 309 288 287 62 1.8k
Jian Qu China 24 1.1k 1.1× 268 0.6× 123 0.4× 104 0.4× 147 0.5× 98 2.0k
Toshihiro Tanioka Japan 14 838 0.8× 331 0.7× 194 0.6× 104 0.4× 189 0.7× 26 2.4k
Julius Leyton United States 30 765 0.8× 211 0.4× 175 0.6× 351 1.2× 179 0.6× 47 2.1k
Jeanette McCarthy United States 23 844 0.8× 187 0.4× 239 0.8× 108 0.4× 544 1.9× 46 2.4k
Yumi Yamamoto Japan 12 701 0.7× 575 1.2× 100 0.3× 118 0.4× 135 0.5× 27 1.7k
Wei Meng China 20 1.0k 1.0× 448 0.9× 164 0.5× 110 0.4× 171 0.6× 45 1.7k
Patrizia Bottoni Italy 21 962 1.0× 388 0.8× 156 0.5× 72 0.3× 210 0.7× 42 1.9k
Leszek Szablewski Poland 21 908 0.9× 373 0.8× 216 0.7× 76 0.3× 140 0.5× 39 1.8k
Maria Cekanova United States 21 563 0.6× 167 0.3× 139 0.4× 100 0.3× 134 0.5× 51 1.7k
Dirk Hendriks Belgium 27 899 0.9× 408 0.8× 111 0.4× 360 1.3× 207 0.7× 96 2.5k

Countries citing papers authored by Ming Lu

Since Specialization
Citations

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

Fields of papers citing papers by Ming Lu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ming Lu

This figure shows the co-authorship network connecting the top 25 collaborators of Ming Lu. A scholar is included among the top collaborators of Ming Lu 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 Lu. Ming Lu 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.
Zeng, Ziqing, Zizhen Zhang, Qing Xie, et al.. (2025). Predicting 177Lu-DOTATATE therapy response through immune microenvironment parameters in gastroenteropancreatic neuroendocrine tumors (GEP-NETs). European Journal of Nuclear Medicine and Molecular Imaging. 53(2). 940–953.
2.
3.
Lu, Ming, et al.. (2024). Distinctive features and prognostic utility of neutrophil in severe patients with Klebsiella pneumoniae infection. Frontiers in Cellular and Infection Microbiology. 14. 1406168–1406168.
4.
Liu, Chao, et al.. (2024). Metastatic infection of hypervirulent Klebsiella pneumoniae. IDCases. 38. e02090–e02090.
5.
Yang, Ping, Chao Liu, Pengcheng Du, et al.. (2024). ST218 Klebsiella pneumoniae became a high-risk clone for multidrug resistance and hypervirulence. BMC Microbiology. 24(1). 56–56.
6.
O’Brien, Neil A., Martina S.J. McDermott, KeWei Gong, et al.. (2023). Development of a Novel CLDN18.2-directed Monoclonal Antibody and Antibody–Drug Conjugate for Treatment of CLDN18.2-Positive Cancers. Molecular Cancer Therapeutics. 22(12). 1365–1375. 5 indexed citations
7.
McDermott, Martina S.J., Neil A. O’Brien, KeWei Gong, et al.. (2023). Preclinical Efficacy of the Antibody–Drug Conjugate CLDN6–23-ADC for the Treatment of CLDN6-Positive Solid Tumors. Clinical Cancer Research. 29(11). 2131–2143. 25 indexed citations
8.
Bränström, Robert, Vladana Vukojević, Ming Lu, et al.. (2023). Ca2+-activated K+ channels modulate membrane potential in the human parathyroid cell: Possible role in exocytosis. Experimental Cell Research. 433(2). 113858–113858.
9.
10.
Yang, Ping, et al.. (2022). Clinical Outcomes and Microbiological Characteristics of Sequence Type 11 Klebsiella pneumoniae Infection. Frontiers in Medicine. 9. 889020–889020. 8 indexed citations
11.
Zhang, Yingmei, Yingmei Wang, Ming Lu, et al.. (2014). Modular Analysis of Bioinformatics Demonstrates a Critical Role for NF-κB in Macrophage Activation. Inflammation. 37(4). 1240–1253. 8 indexed citations
12.
Huang, Yongming, Weiliang Xia, Ming Lu, et al.. (2014). Role of Kinase Epidermal Growth Factor Receptor and SRC in the Caerulein-Induced Acute Pancreatitis in Mice. Pancreas. 44(1). 152–157. 4 indexed citations
13.
Gao, Bo, Ming Lu, Xianzhi Meng, et al.. (2014). Database screening of herbal monomers regulating autophagy by constructing a "disease-gene-drug" network. BMC Complementary and Alternative Medicine. 14(1). 466–466. 1 indexed citations
14.
Lu, Ming, et al.. (2013). Proteomic analysis of apoptotic and oncotic pancreatic acinar AR42J cells treated with caerulein. Molecular and Cellular Biochemistry. 382(1-2). 1–17. 18 indexed citations
15.
Xue, Dongbo, Ming Lu, Bo Gao, Xin Qiao, & Yingmei Zhang. (2013). Screening for transcription factors and their regulatory small molecules involved in regulating the functions of CL1-5 cancer cells under the effects of macrophage-conditioned medium. Oncology Reports. 31(3). 1323–1333. 6 indexed citations
16.
Kalous, Ondrej, Dylan Conklin, Amrita Desai, et al.. (2013). AMG 900, pan-Aurora kinase inhibitor, preferentially inhibits the proliferation of breast cancer cell lines with dysfunctional p53. Breast Cancer Research and Treatment. 141(3). 397–408. 22 indexed citations
17.
Zhang, Yingmei, Dongbo Xue, Xiaochun Wang, et al.. (2013). Screening of kinase inhibitors targeting BRAF for regulating autophagy based on kinase pathways. Molecular Medicine Reports. 9(1). 83–90. 26 indexed citations
18.
Whelan, Stephen A., Ming Lu, Jianbo He, et al.. (2008). Mass spectrometry (LC-MS/MS) analysis of proximal fluid and cell membrane proteins for breast cancer biomarkers. Cancer Research. 68. 4436–4436. 3 indexed citations
19.
Lu, Ming. (2001). Provider encouragement of breast-feeding: evidence from a national survey. Obstetrics and Gynecology. 97(2). 290–295. 140 indexed citations
20.
Lu, Ming, et al.. (1996). Retrovirus-Mediated Gene Expression in Hematopoietic Cells Correlates Inversely with Growth Factor Stimulation. Human Gene Therapy. 7(18). 2263–2271. 26 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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