Wei Ma

1.7k citations
82 papers · 1.3k · h-index 21

Impact in

    • MicroRNA in disease regulation
    • Cancer-related molecular mechanisms research
    • Circular RNAs in diseases
    • RNA modifications and cancer
    • Natural product bioactivities and synthesis

Papers in

    • MicroRNA in disease regulation 9
    • Cancer-related molecular mechanisms research 7
    • Circular RNAs in diseases 6
    • RNA modifications and cancer 5

Wei Ma

79 papers receiving 1.3k citations

Peers

Wei Ma
Comparison fields: 5 of 118
  • Cancer Research 248
  • Molecular Biology 508
  • Biochemistry 39
  • Rheumatology 75
  • Genetics 51
Replace Yang Tan with:
Yang Tan China
Weiping Wang China
Jaideep Banerjee United States
Yukai Huang China
Xu D China
Lingling Jiang China
Lei Dai China
Yulai Zhou China
Kakali Sarkar United States
Wei Ma relative to Yang Tan China Yang Tan's profile →
Citations per field
00.5×2×3×
Yang Tan · 1×
Citations per year

Countries citing papers authored by Wei Ma

Since Specialization
Citations

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

Fields of papers citing papers by Wei Ma

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 82 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2014120
2 201274
3 201553
4 202045
5 201839
6 201739
7 201638
8 201734
9 202133
10
Bone sialoprotein promotes bone metastasis of a non-bone-seeking clone of human breast cancer cells.
200432
11 201831
12 200729
13 200926
14 202126
15 202225
16 202425
17 201424
18 201924
19 201624
20 202024

About Wei Ma

Wei Ma is a scholar working on Cancer Research, Molecular Biology, Genetics, Rheumatology and Oral Surgery, having authored 82 papers that have together received 1.3k indexed citations. Recurring topics across this work include Spinal Dysraphism and Malformations (9 papers), MicroRNA in disease regulation (9 papers), Cancer-related molecular mechanisms research (7 papers), Circular RNAs in diseases (6 papers), Bone Tissue Engineering Materials (6 papers), RNA modifications and cancer (5 papers), Mesenchymal stem cell research (5 papers) and Dental Implant Techniques and Outcomes (5 papers). The work is most often cited by research in Cancer Research (248 citations), Molecular Biology (508 citations), Biochemistry (39 citations), Rheumatology (75 citations) and Genetics (51 citations). Wei Ma has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Zhengwei Yuan, Xiaowei Wei, Hui Fang Gu, Dan Liu, Kai‐Jin Wang, Songying Cao, Guoqing Yan, Tianchu Huang, Yong‐Xian Cheng and Ning Li. Their work appears in journals such as Cell Death and Disease, Journal of Biomedical Materials Research Part B Applied Biomaterials, Frontiers in Cell and Developmental Biology, Oncology Reports and Surface and Coatings Technology.

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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