Dejing Pan

923 citations
35 papers · 669 · h-index 14

Impact in

Papers in

    • Pluripotent Stem Cells Research 3
    • 3D Printing in Biomedical Research 5
    • Microfluidic and Bio-sensing Technologies 5
    • Microfluidic and Capillary Electrophoresis Applications 4

Dejing Pan

35 papers receiving 647 citations

Peers

Dejing Pan
Comparison fields: 5 of 98
  • Developmental Biology 15
  • Paleontology 45
  • Social Psychology 95
  • Genetics 115
  • Aging 7
Replace Ondřej Podlaha with:
Ondřej Podlaha United States
Marilyn A. Mitchell United States
Christopher M. Smith United States
Deena Emera United States
Rachel M. Gittelman United States
Michaela Neusser Germany
Jean‐Luc Fausser France
Shintaroh Ueda Japan
Oscar A. Tarazona United States
Tetsuya Bando Japan
Dejing Pan relative to Ondřej Podlaha United States Ondřej Podlaha's profile →
Citations per field
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Ondřej Podlaha · 1×
Citations per year

Countries citing papers authored by Dejing Pan

Since Specialization
Citations

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

Fields of papers citing papers by Dejing Pan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 35 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1994130
2 199383
3 201563
4 202160
5 201243
6 201429
7 201821
8 201620
9 200319
10 201918
11 200718
12 201715
13 202114
14 200313
15 202213
16 200212
17 201911
18 201810
19
[Determination of HLA-DRB1 gene polymorphism by PCR-SBT in Lahu ethnic group of Yunnan, China].
200210
20 20219

About Dejing Pan

Dejing Pan is a scholar working on Molecular Biology, Biomedical Engineering, Immunology, Plant Science and Cell Biology, having authored 35 papers that have together received 669 indexed citations. Recurring topics across this work include T-cell and B-cell Immunology (7 papers), Immune Cell Function and Interaction (7 papers), 3D Printing in Biomedical Research (5 papers), Microfluidic and Bio-sensing Technologies (5 papers), Microfluidic and Capillary Electrophoresis Applications (4 papers), Immune Response and Inflammation (3 papers), Biochemical and biochemical processes (3 papers) and Pluripotent Stem Cells Research (3 papers). The work is most often cited by research in Developmental Biology (15 citations), Paleontology (45 citations), Social Psychology (95 citations), Genetics (115 citations) and Aging (7 citations). Dejing Pan has collaborated with scholars based in China, Switzerland and United States. Frequent co-authors include Sarah Zehr, Maryellen Ruvolo, Tony L. Goldberg, Todd R. Disotell, Zhen Zhu, Jonathan Y. Lin, Bong‐Soon Chang, Yoshikuni Nagamine, Janice Ching Lai and Zehuan Liu. Their work appears in journals such as Blood, Electrophoresis, Sensors and Actuators B Chemical, Human Immunology and Analytical and Bioanalytical Chemistry.

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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