Ming D. Li

8.4k total citations
179 papers, 5.8k citations indexed

About

Ming D. Li is a scholar working on Molecular Biology, Physiology and Genetics. According to data from OpenAlex, Ming D. Li has authored 179 papers receiving a total of 5.8k indexed citations (citations by other indexed papers that have themselves been cited), including 116 papers in Molecular Biology, 47 papers in Physiology and 42 papers in Genetics. Recurrent topics in Ming D. Li's work include Nicotinic Acetylcholine Receptors Study (67 papers), Smoking Behavior and Cessation (40 papers) and Genetic Associations and Epidemiology (27 papers). Ming D. Li is often cited by papers focused on Nicotinic Acetylcholine Receptors Study (67 papers), Smoking Behavior and Cessation (40 papers) and Genetic Associations and Epidemiology (27 papers). Ming D. Li collaborates with scholars based in United States, China and South Korea. Ming D. Li's co-authors include Z. Jennie, Thomas J. Payne, Weihua Huang, Robert C. Elston, Xiang‐Yang Lou, Joke Beuten, Zhongli Yang, Guo‐Bo Chen, Gary E. Swan and Rong Cheng and has published in prestigious journals such as Journal of Biological Chemistry, Journal of Neuroscience and PLoS ONE.

In The Last Decade

Ming D. Li

174 papers receiving 5.7k 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 D. Li United States 42 3.0k 1.5k 1.3k 1.1k 648 179 5.8k
Andrew N. Margioris Greece 48 1.8k 0.6× 941 0.6× 875 0.7× 505 0.4× 715 1.1× 145 7.5k
Aldo E. Calogero Italy 60 2.4k 0.8× 836 0.6× 721 0.6× 1.2k 1.1× 526 0.8× 502 13.5k
Tao Lu China 27 3.4k 1.1× 2.1k 1.4× 928 0.7× 440 0.4× 1.2k 1.8× 111 7.3k
Günter K. Stalla Germany 60 2.5k 0.8× 1.3k 0.9× 1.2k 0.9× 840 0.7× 1.5k 2.3× 306 13.5k
Adriana Maggi Italy 60 3.3k 1.1× 1.4k 1.0× 1.8k 1.4× 3.7k 3.3× 937 1.4× 217 11.6k
Toshikazu Saito Japan 42 2.7k 0.9× 1.2k 0.8× 1.5k 1.1× 491 0.4× 440 0.7× 315 6.7k
Matthew B. McQueen United States 34 1.9k 0.6× 1.6k 1.0× 717 0.5× 1.2k 1.1× 362 0.6× 82 5.2k
Marco Fiore Italy 47 1.3k 0.4× 898 0.6× 1.5k 1.2× 366 0.3× 564 0.9× 257 6.3k
Robert H. Lipsky United States 44 2.6k 0.9× 743 0.5× 2.5k 1.9× 806 0.7× 563 0.9× 112 8.1k

Countries citing papers authored by Ming D. Li

Since Specialization
Citations

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

Fields of papers citing papers by Ming D. Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ming D. Li

This figure shows the co-authorship network connecting the top 25 collaborators of Ming D. Li. A scholar is included among the top collaborators of Ming D. Li 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 D. Li. Ming D. Li 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.
Bao, Zhiwei, et al.. (2025). MultiTax-human: an extensive and high-resolution human-related full-length 16S rRNA reference database and taxonomy. Microbiology Spectrum. 13(2). e0131224–e0131224.
2.
Wang, Yan, Zhongli Yang, Haijun Han, et al.. (2025). Investigating the effect of Arvcf reveals an essential role on regulating the mesolimbic dopamine signaling-mediated nicotine reward. Communications Biology. 8(1). 429–429.
3.
Han, Haijun, Guoliang Chen, Bin Zhang, et al.. (2024). Probiotic Lactobacillus plantarum GUANKE effectively alleviates allergic rhinitis symptoms by modulating functions of various cytokines and chemokines. Frontiers in Nutrition. 10. 1291100–1291100. 9 indexed citations
4.
Dang, Li, Minghao Li, Kai-Lun Hu, et al.. (2024). Integrative multiomics analysis reveals association of gut microbiota and its metabolites with susceptibility to keloids. Frontiers in Microbiology. 15. 1475984–1475984. 1 indexed citations
5.
6.
Li, Ming D., Minghao Li, Li Dang, et al.. (2023). 16S rRNA gene sequencing reveals the correlation between the gut microbiota and the susceptibility to pathological scars. Frontiers in Microbiology. 14. 1215884–1215884. 4 indexed citations
7.
Zhu, Zhouhai, Qiang Liu, Meng Li, et al.. (2023). Determination of genetic correlation between tobacco smoking and coronary artery disease. Frontiers in Psychiatry. 14. 1279962–1279962. 2 indexed citations
8.
Chen, Chujun, Zhening Liu, Chang Xi, et al.. (2021). Decreased Cortical Folding of the Fusiform Gyrus and Its Hypoconnectivity with Sensorimotor Areas in Major Depressive Disorder. Journal of Affective Disorders. 295. 657–664. 37 indexed citations
9.
Yang, Zhongli, et al.. (2021). Correlation Between Prognostic Biomarker SLC1A5 and Immune Infiltrates in Various Types of Cancers Including Hepatocellular Carcinoma. Frontiers in Oncology. 11. 608641–608641. 19 indexed citations
10.
Li, Dawei, Hongyu Zhao, Henry R. Kranzler, et al.. (2014). Genome-Wide Association Study of Copy Number Variations (CNVs) with Opioid Dependence. Neuropsychopharmacology. 40(4). 1016–1026. 36 indexed citations
11.
Hser, Yih‐Ing, Linda Chang, Gene‐Jack Wang, et al.. (2013). Capacity building and collaborative research on cross-national studies in the Asian region. Journal of Food and Drug Analysis. 21(4). S117–S122. 3 indexed citations
12.
Yang, Zhongli, Lin Chen, Shaolin Wang, et al.. (2013). Determination of allelic expression of SNP rs1880676 in choline acetyltransferase gene in HeLa cells. Neuroscience Letters. 555. 215–219. 1 indexed citations
13.
Yang, Shigui, Bing Wang, Ping Chen, et al.. (2012). Effectiveness of HBV Vaccination in Infants and Prediction of HBV Prevalence Trend under New Vaccination Plan: Findings of a Large-Scale Investigation. PLoS ONE. 7(10). e47808–e47808. 27 indexed citations
14.
Cui, Wenyan, Chamindi Seneviratne, Jun Gu, & Ming D. Li. (2011). Genetics of GABAergic signaling in nicotine and alcohol dependence. Human Genetics. 131(6). 843–855. 26 indexed citations
15.
Cao, Junran, Jennifer B. Dwyer, Wang Ju, et al.. (2010). Modulation of cell adhesion systems by prenatal nicotine exposure in limbic brain regions of adolescent female rats. The International Journal of Neuropsychopharmacology. 14(2). 157–174. 23 indexed citations
16.
Li, Ming D.. (2010). Grand challenges and opportunities for molecular psychiatry research: A perspective. Frontiers in Psychiatry. 1. 2–2. 7 indexed citations
17.
18.
Xu, Qing, Weihua Huang, Thomas J. Payne, Z. Jennie, & Ming D. Li. (2008). Detection of Genetic Association and a Functional Polymorphism of Dynamin 1 Gene with Nicotine Dependence in European and African Americans. Neuropsychopharmacology. 34(5). 1351–1359. 12 indexed citations
19.
Li, Ming D., et al.. (2008). Gene-Gene Interactions Among CHRNA4, CHRNB2, BDNF, and NTRK2 in Nicotine Dependence. Biological Psychiatry. 64(11). 951–957. 51 indexed citations
20.
Liu, Pengchong, Jianxi Liu, Weihua Huang, Ming D. Li, & Alejandro M. Dopico. (2003). Distinct Regions of the slo Subunit Determine Differential BKCa Channel Responses to Ethanol. Alcoholism Clinical and Experimental Research. 27(10). 1640–1644. 20 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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