Jun Lao

537 citations
12 papers · 483 · h-index 8

Impact in

    • Carbon and Quantum Dots Applications
    • Nanocluster Synthesis and Applications
    • Graphene research and applications
    • Graphene and Nanomaterials Applications
    • Nanoplatforms for cancer theranostics

Papers in

    • Receptor Mechanisms and Signaling 3
    • RNA Interference and Gene Delivery 2
    • Chemokine receptors and signaling 5

Jun Lao

12 papers receiving 476 citations

Peers

Jun Lao
Comparison fields: 5 of 60
  • Materials Chemistry 297
  • Biomedical Engineering 245
  • Biophysics 21
  • Biomaterials 44
  • Molecular Biology 169
Replace Evgenii L. Guryev with:
Evgenii L. Guryev Russia
Xingfu Zhu China
Mingxi Zhang China
Jack J. Li United States
L. Anasagasti Cuba
M.W. Hayman United Kingdom
Sarmistha Nanda United States
Felice Shieh United States
Eleonora Muro France
Ze‐Rui Zhou China
Jun Lao relative to Evgenii L. Guryev Russia Evgenii L. Guryev's profile →
Citations per field
00.5×10×20×30×40×46×
Evgenii L. Guryev · 1×
Citations per year

Countries citing papers authored by Jun Lao

Since Specialization
Citations

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

Fields of papers citing papers by Jun Lao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

12 of 12 papers shown
#Work
1 2014289
2 201543
3 201739
4 201731
5 201920
6 201319
7 202016
8 201714
9 20166
10 20173
11 20172
12 20251

About Jun Lao

Jun Lao is a scholar working on Molecular Biology, Oncology, Immunology, Radiology, Nuclear Medicine and Imaging and Biomedical Engineering, having authored 12 papers that have together received 483 indexed citations. Recurring topics across this work include Chemokine receptors and signaling (5 papers), Immunotherapy and Immune Responses (3 papers), Receptor Mechanisms and Signaling (3 papers), Monoclonal and Polyclonal Antibodies Research (3 papers), Graphene and Nanomaterials Applications (2 papers), T-cell and B-cell Immunology (2 papers), RNA Interference and Gene Delivery (2 papers) and Carbon and Quantum Dots Applications (2 papers). The work is most often cited by research in Materials Chemistry (297 citations), Biomedical Engineering (245 citations), Biophysics (21 citations), Biomaterials (44 citations) and Molecular Biology (169 citations). Jun Lao has collaborated with scholars based in China, Portugal and India. Frequent co-authors include Fang Huang, Hua He, Xiaojuan Wang, Xing Sun, Tiantian Cheng, Shengjie Wang, Baosheng Ge, Jiqiang Li, Yao Chen and Yongqing Xia. Their work appears in journals such as Colloids and Surfaces B Biointerfaces, PLoS ONE, Chemistry - A European Journal, Process Biochemistry and Scientific Reports.

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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