Jun Mao

2.7k citations
46 papers · 1.8k · h-index 24

Impact in

    • MicroRNA in disease regulation
    • Cancer-related molecular mechanisms research
  • Oncology top 5%
    • Cancer Cells and Metastasis

Papers in

    • Epigenetics and DNA Methylation 6
    • Wnt/β-catenin signaling in development and cancer 4
    • Circular RNAs in diseases 4
    • Hedgehog Signaling Pathway Studies 4
    • Mechanisms of cancer metastasis 3
    • Cancer Cells and Metastasis 10

Jun Mao

45 papers receiving 1.8k citations

Peers

Jun Mao
Comparison fields: 5 of 94
  • Cancer Research 623
  • Oncology 482
  • Molecular Biology 1.2k
  • Geriatrics and Gerontology 32
  • Pathology and Forensic Medicine 107
Replace Leina Ma with:
Leina Ma China
Flore Kruiswijk United States
Francesca Bruzzese Italy
Brandon J. Aubrey Australia
Xinchen Sun China
Helena Pópulo Portugal
Xisong Ke China
Călin Ionescu Romania
Lijun Di China
Yongdong Feng China
Jun Mao relative to Leina Ma China Leina Ma's profile →
Citations per field
00.5×1.7×
Leina Ma · 1×
Citations per year

Countries citing papers authored by Jun Mao

Since Specialization
Citations

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

Fields of papers citing papers by Jun Mao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 46 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2014217
2 2017136
3 2019114
4 2013107
5 2017100
6 201899
7 202093
8 201883
9 201677
10 201566
11 201263
12 201862
13 202161
14 201450
15 202140
16 201838
17 201331
18 201930
19 202129
20 201426

About Jun Mao

Jun Mao is a scholar working on Molecular Biology, Oncology, Cancer Research, Immunology and Pathology and Forensic Medicine, having authored 46 papers that have together received 1.8k indexed citations. Recurring topics across this work include Cancer Cells and Metastasis (10 papers), Epigenetics and DNA Methylation (6 papers), MicroRNA in disease regulation (6 papers), Cancer-related molecular mechanisms research (5 papers), Wnt/β-catenin signaling in development and cancer (4 papers), Circular RNAs in diseases (4 papers), Hedgehog Signaling Pathway Studies (4 papers) and Mechanisms of cancer metastasis (3 papers). The work is most often cited by research in Cancer Research (623 citations), Oncology (482 citations), Molecular Biology (1.2k citations), Geriatrics and Gerontology (32 citations) and Pathology and Forensic Medicine (107 citations). Jun Mao has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Ying Lü, Bo Song, Tao Qin, Lianhong Li, Xiaotang Yu, Lianhong Li, Shujun Fan, L Wang, Qun Zhang and Qingqing Zhang. Their work appears in journals such as Biomedicine & Pharmacotherapy, Chemico-Biological Interactions, Cell Death and Disease, Journal of Experimental & Clinical Cancer Research and International Journal of Molecular Sciences.

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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