Min Shen

12.8k citations
162 papers · 7.2k indexed · 3 hit papers · h-index 42

Min Shen

156 papers receiving 7.0k citations

Hit Papers

Remdesivir: A Review ...6542003202620102018250500750

Peers

Min Shen
Comparison fields: 5 of 167
  • Computational Theory and Mathematics 1.5k
  • Cancer Research 1.2k
  • Infectious Diseases 1.1k
  • Molecular Biology 3.8k
  • Oncology 879
Replace Cheng Luo with:
Cheng Luo China
Ajit Jadhav United States
Anton Simeonov United States
Mingzhu Yin China
Ruili Huang United States
Irina Massova United States
Patrick A. Eyers United Kingdom
David B. Ascher Australia
Asimul Islam India
Tarun Jha India
Min Shen relative to Cheng Luo China Cheng Luo's profile →
Citations per field
00.5×1.5×2.1×
Cheng Luo · 1×
Citations per year

Countries citing papers authored by Min Shen

Since Specialization
Citations

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

Fields of papers citing papers by Min Shen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Min Shen, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Min Shen Line = papers co-authored together Min Shen links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20251
2 202311
3 20231
4 20231
5 20227
6 20229
7 20228
8 20218
9 202120
10 202110
11 202018
12 201922
13 201922
14 201913
15 201677
16 201616
17 2014198
18 201273
19
Toward Improved Therapy for Classic Galactosemia
20112
20 2010148

About Min Shen

Min Shen is a scholar working on Cancer Research, Computational Theory and Mathematics and Biochemistry, having authored 162 papers that have together received 7.2k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (26 papers), Cancer, Hypoxia, and Metabolism (21 papers), SARS-CoV-2 and COVID-19 Research (16 papers), Biochemical and Molecular Research (11 papers), COVID-19 Clinical Research Studies (10 papers), Ubiquitin and proteasome pathways (8 papers), Cancer-related Molecular Pathways (8 papers) and Amino Acid Enzymes and Metabolism (8 papers). The work is most often cited by research in Computational Theory and Mathematics (1.5k citations), Cancer Research (1.2k citations) and Infectious Diseases (1.1k citations). Min Shen has collaborated with scholars based in United States, China and Germany. Frequent co-authors include Anton Simeonov, Douglas S. Auld, Matthew D. Hall, Alexander Tropsha, Alexander Golbraikh, Craig J. Thomas, Matthew B. Boxer, Kyle R. Brimacombe, Richard T. Eastman and Samarjit Patnaik. Their work appears in journals such as Journal of Medicinal Chemistry, Bioorganic & Medicinal Chemistry Letters, ACS Pharmacology & Translational Science, PLoS ONE and Cancer Research.

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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