Ming Guan

5.2k citations
189 papers · 4.0k · h-index 37

Impact in

    • Cancer-related molecular mechanisms research
    • MicroRNA in disease regulation
    • Circular RNAs in diseases
    • Extracellular vesicles in disease
    • RNA modifications and cancer
    • Epigenetics and DNA Methylation
    • Angiogenesis and VEGF in Cancer

Papers in

    • Epigenetics and DNA Methylation 12
    • Advanced biosensing and bioanalysis techniques 10
    • Angiogenesis and VEGF in Cancer 10

Ming Guan

178 papers receiving 4.0k citations

Peers

Ming Guan
Comparison fields: 5 of 146
  • Cancer Research 980
  • Molecular Biology 2.0k
  • Immunology 486
  • Dermatology 200
  • Genetics 215
Replace Mutsuo Furihata with:
Mutsuo Furihata Japan
Byeong‐Cheol Ahn South Korea
Keiji Inoue Japan
Philipp Ströbel Germany
Vincenza Dolo Italy
Léon C.L.T. van Kempen Netherlands
Mario Del Rosso Italy
Yunmei Wang United States
Karl G. Csaky United States
Xuan Wang China
Ming Guan relative to Mutsuo Furihata Japan Mutsuo Furihata's profile →
Citations per field
00.5×
Mutsuo Furihata · 1×
Citations per year

Countries citing papers authored by Ming Guan

Since Specialization
Citations

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

Fields of papers citing papers by Ming Guan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 189 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2010186
2 2019183
3 2020146
4 2016121
5 2012106
6 2003104
7 201881
8 200980
9 200278
10 200673
11 200468
12 200368
13 200464
14 200855
15 200454
16 201153
17 200952
18 201950
19 202049
20 201947

About Ming Guan

Ming Guan is a scholar working on Molecular Biology, Immunology, Genetics, Cancer Research and Oncology, having authored 189 papers that have together received 4.0k indexed citations. Recurring topics across this work include Myeloproliferative Neoplasms: Diagnosis and Treatment (14 papers), Epigenetics and DNA Methylation (12 papers), Advanced biosensing and bioanalysis techniques (10 papers), Angiogenesis and VEGF in Cancer (10 papers), CNS Lymphoma Diagnosis and Treatment (10 papers), Cancer Genomics and Diagnostics (10 papers), Eosinophilic Disorders and Syndromes (9 papers) and Lymphoma Diagnosis and Treatment (9 papers). The work is most often cited by research in Cancer Research (980 citations), Molecular Biology (2.0k citations), Immunology (486 citations), Dermatology (200 citations) and Genetics (215 citations). Ming Guan has collaborated with scholars based in China, Hong Kong and United States. Frequent co-authors include Xinju Zhang, Yuan Lu, Jun Wan, Zhiyuan Wu, Zhihua Kang, Xuan Deng, Haoyu Ruan, Bo Yu, Ji Jin and Xiao Xu. Their work appears in journals such as Clinica Chimica Acta, PLoS ONE, Scientific Reports, Clinical Rheumatology and BioMed Research International.

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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