Minjun Chen

5.6k total citations · 2 hit papers
104 papers, 4.0k citations indexed

About

Minjun Chen is a scholar working on Pharmacology, Molecular Biology and Epidemiology. According to data from OpenAlex, Minjun Chen has authored 104 papers receiving a total of 4.0k indexed citations (citations by other indexed papers that have themselves been cited), including 46 papers in Pharmacology, 30 papers in Molecular Biology and 26 papers in Epidemiology. Recurrent topics in Minjun Chen's work include Drug-Induced Hepatotoxicity and Protection (40 papers), Pharmacogenetics and Drug Metabolism (34 papers) and Computational Drug Discovery Methods (24 papers). Minjun Chen is often cited by papers focused on Drug-Induced Hepatotoxicity and Protection (40 papers), Pharmacogenetics and Drug Metabolism (34 papers) and Computational Drug Discovery Methods (24 papers). Minjun Chen collaborates with scholars based in United States, China and Germany. Minjun Chen's co-authors include Weida Tong, Jürgen Borlak, Ayako Suzuki, Hong Fang, Huixiao Hong, Hui Wang, Shraddha Thakkar, M. Isabel Lucena, Raúl J. Andrade and Ke Yu and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Biomaterials.

In The Last Decade

Minjun Chen

98 papers receiving 3.9k citations

Hit Papers

FDA-approved drug labeling for the study of drug-induced ... 2011 2026 2016 2021 2011 2016 50 100 150 200 250

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Minjun Chen United States 35 1.5k 1.2k 893 624 441 104 4.0k
Lauren M. Aleksunes United States 48 1.4k 1.0× 2.8k 2.3× 374 0.4× 1.0k 1.6× 108 0.2× 168 7.0k
Manthena V. S. Varma United States 44 2.1k 1.4× 1.0k 0.9× 635 0.7× 402 0.6× 98 0.2× 127 5.7k
Taimour Langaee United States 37 2.5k 1.7× 1.5k 1.2× 313 0.4× 361 0.6× 192 0.4× 152 5.5k
Neil Parrott Switzerland 37 1.5k 1.0× 1.0k 0.9× 516 0.6× 266 0.4× 71 0.2× 125 4.5k
Xiaohe Xiao China 45 2.7k 1.8× 3.9k 3.2× 236 0.3× 903 1.4× 128 0.3× 396 8.6k
Thierry Lavé Switzerland 35 1.3k 0.9× 682 0.6× 485 0.5× 203 0.3× 56 0.1× 68 3.0k
Allen H. Heller United States 21 494 0.3× 582 0.5× 286 0.3× 269 0.4× 188 0.4× 48 2.5k
Richard D. Beger United States 40 773 0.5× 3.2k 2.6× 408 0.5× 495 0.8× 50 0.1× 163 5.8k
Eric Chun Yong Chan Singapore 41 854 0.6× 3.1k 2.5× 165 0.2× 297 0.5× 76 0.2× 186 5.5k
Xiao Ma China 40 1.0k 0.7× 2.3k 1.9× 97 0.1× 812 1.3× 223 0.5× 261 5.4k

Countries citing papers authored by Minjun Chen

Since Specialization
Citations

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

Fields of papers citing papers by Minjun Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Minjun Chen

This figure shows the co-authorship network connecting the top 25 collaborators of Minjun Chen. A scholar is included among the top collaborators of Minjun Chen 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 Minjun Chen. Minjun Chen 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.
Chen, Minjun, et al.. (2025). New approach methodologies (NAMs) for drug-induced liver injury (DILI): Where are we now?. Drug Discovery Today. 30(9). 104452–104452. 2 indexed citations
2.
Niu, Hao, Ismael Álvarez‐Álvarez, & Minjun Chen. (2025). Artificial Intelligence: An Emerging Tool for Studying Drug‐Induced Liver Injury. Liver International. 45(3). e70038–e70038. 2 indexed citations
3.
Chen, Minjun, L. Huang, Li Chen, et al.. (2025). Construction of a Palliative Care Services Framework for End‐of‐Life Adult Patients at Medical Institutions: A Delphi Study. European Journal of Cancer Care. 2025(1).
5.
Zhao, Jinwen, et al.. (2024). Drug interaction with UDP-Glucuronosyltransferase (UGT) enzymes is a predictor of drug-induced liver injury. Hepatology. 81(5). 1512–1521. 5 indexed citations
6.
Crosby, Lynn M., et al.. (2024). Medical device report analyses from MAUDE: Device and patient outcomes, adverse events, and sex-based differential effects. Regulatory Toxicology and Pharmacology. 149. 105591–105591. 2 indexed citations
7.
Chen, Minjun, et al.. (2019). MicroRNA-138 negatively regulates the hypoxia-inducible factor 1α to suppress melanoma growth and metastasis. Biology Open. 8(8). 16 indexed citations
9.
Wu, Leihong, Zhichao Liu, Joshua Xu, et al.. (2015). NETBAGs: A Network-Based Clustering Approach with Gene Signatures for Cancer Subtyping Analysis. Biomarkers in Medicine. 9(11). 1053–1065. 7 indexed citations
10.
Hawser, Stephen, Samuel K. Bouchillon, Meredith Hackel, Minjun Chen, & Eui-Chong Kim. (2012). Trending 7 years of in vitro activity of tigecycline and comparators against Gram-positive and Gram-negative pathogens from the Asia-Pacific region: Tigecycline Evaluation Surveillance Trial (TEST) 2004–2010. International Journal of Antimicrobial Agents. 39(6). 490–495. 9 indexed citations
11.
Zhao, Chunjiang, Hongli Sun, Hui Wang, et al.. (2012). Antimicrobial resistance trends among 5608 clinical Gram-positive isolates in China: results from the Gram-Positive Cocci Resistance Surveillance program (2005–2010). Diagnostic Microbiology and Infectious Disease. 73(2). 174–181. 59 indexed citations
12.
Chen, Minjun, Vikrant Vijay, Qiang Shi, et al.. (2011). FDA-approved drug labeling for the study of drug-induced liver injury. Drug Discovery Today. 16(15-16). 697–703. 296 indexed citations breakdown →
13.
Yang, Qiwen, Hui Wang, Hongli Sun, et al.. (2009). Phenotypic and Genotypic Characterization of Enterobacteriaceae with Decreased Susceptibility to Carbapenems: Results from Large Hospital-Based Surveillance Studies in China. Antimicrobial Agents and Chemotherapy. 54(1). 573–577. 65 indexed citations
14.
Wang, Hui & Minjun Chen. (2009). The microbiology laboratory should intensively cooperate with the clinicians to improve the diagnostic level of pulmonary infections. Zhonghua jianyan yixue zazhi. 32(3). 245–248. 1 indexed citations
15.
Chen, Hongbin, et al.. (2009). The molecular characteristics of heteroresistant vancomycin-intermediate Staphylococcus aureus in China. Zhonghua jianyan yixue zazhi. 32(11). 1223–1227. 2 indexed citations
16.
Chen, Minjun. (2009). Antimicrobial Resistance Surveillance on Hospital-and Community-acquired Pathogens in 10 Teaching Hospitals in China. Zhongguo yiyuan ganranxue zazhi. 1 indexed citations
17.
Qiu, Yunping, Minjun Chen, Guoxiang Xie, et al.. (2008). Metabolic profiling reveals therapeutic effects of Herba Cistanches in an animal model of hydrocortisone-induced 'kidney-deficiency syndrome'. Chinese Medicine. 3(1). 3–3. 29 indexed citations
18.
Schnackenberg, Laura K., Minjun Chen, Jinchun Sun, et al.. (2008). Evaluations of the trans-sulfuration pathway in multiple liver toxicity studies. Toxicology and Applied Pharmacology. 235(1). 25–32. 28 indexed citations
19.
Ni, Yan, Mingming Su, Yunping Qiu, et al.. (2007). Metabolic profiling using combined GC–MS and LC–MS provides a systems understanding of aristolochic acid‐induced nephrotoxicity in rat. FEBS Letters. 581(4). 707–711. 92 indexed citations
20.
Chen, Minjun. (2002). Resistance mechanism of erythromycin in Streptococcus pneumoniae. Zhonghua jianyan yixue zazhi. 1 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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