Lie Min

1.0k citations
25 papers · 796 · h-index 15

Impact in

Papers in

Lie Min

25 papers receiving 788 citations

Peers

Lie Min
Comparison fields: 5 of 85
  • Molecular Biology 608
  • Radiology, Nuclear Medicine and Imaging 157
  • Neurology 55
  • Immunology 139
  • Genetics 47
Replace Ajay Sharma with:
Ajay Sharma India
Emily E. Brown United States
Aline Appert-Collin France
Divya Khaitan India
Jerry Di Salvo United States
Koichi Tamoto Japan
Xiaoping Hronowski United States
Nicolas Currier United States
Marco Trinchera Italy
Jabari Brown United States
Lie Min relative to Ajay Sharma India Ajay Sharma's profile →
Citations per field
00.5×3.4×
Ajay Sharma · 1×
Citations per year

Countries citing papers authored by Lie Min

Since Specialization
Citations

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

Fields of papers citing papers by Lie Min

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Lie Min, 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 Lie Min Line = papers co-authored together Lie Min links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 25 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2016160
2 2013132
3 2012106
4 201669
5 200738
6 201534
7 200734
8 200927
9 201626
10 200526
11 202220
12 202316
13 201515
14 202215
15 200914
16 201014
17 201513
18 202310
19 202310
20 20245

About Lie Min

Lie Min is a scholar working on Molecular Biology, Radiology, Nuclear Medicine and Imaging, Oncology, Immunology and Genetics, having authored 25 papers that have together received 796 indexed citations. Recurring topics across this work include Protein purification and stability (8 papers), Viral Infectious Diseases and Gene Expression in Insects (8 papers), Monoclonal and Polyclonal Antibodies Research (7 papers), Cytokine Signaling Pathways and Interactions (3 papers), Glycosylation and Glycoproteins Research (3 papers), T-cell and B-cell Immunology (3 papers), Signaling Pathways in Disease (2 papers) and Virus-based gene therapy research (2 papers). The work is most often cited by research in Molecular Biology (608 citations), Radiology, Nuclear Medicine and Imaging (157 citations), Neurology (55 citations), Immunology (139 citations) and Genetics (47 citations). Lie Min has collaborated with scholars based in United States, Germany and United Kingdom. Frequent co-authors include Kelvin H. Lee, Amy H. Andreotti, R Joseph, Abraham M. Lenhoff, Kristin N. Valente, Constantine D. Tsoukas, Roman M. Levytskyy, D. Bruce Fulton, Richard W. Kriwacki and Christy R. Grace. Their work appears in journals such as Biotechnology and Bioengineering, Journal of Molecular Biology, Biochemistry, Electrophoresis and Frontiers in bioscience.

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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