Muliang Ding

838 citations
29 papers · 623 · h-index 13

Impact in

Papers in

    • Circular RNAs in diseases 5
    • RNA Research and Splicing 2
    • Extracellular vesicles in disease 2
    • MicroRNA in disease regulation 6
    • Cancer-related molecular mechanisms research 4

Muliang Ding

29 papers receiving 615 citations

Peers

Muliang Ding
Comparison fields: 5 of 86
  • Cancer Research 188
  • Geriatrics and Gerontology 15
  • Rehabilitation 28
  • Molecular Biology 294
  • Epidemiology 124
Replace Deye Song with:
Deye Song China
Keun Koo Shin South Korea
Liming Yu China
Fei Pei China
Michael Cangkrama Switzerland
Abdul S. Qadir South Korea
Leilei Zhang China
Meng Fan China
Ryan A. Denu United States
Ranyue Ren China
Muliang Ding relative to Deye Song China Deye Song's profile →
Citations per field
00.5×1.5×
Deye Song · 1×
Citations per year

Countries citing papers authored by Muliang Ding

Since Specialization
Citations

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

Fields of papers citing papers by Muliang Ding

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 29 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2017111
2 201593
3 202357
4
AMPK: implications in osteoarthritis and therapeutic targets.
202041
5 201136
6 201531
7
Activation of unfolded protein response protects osteosarcoma cells from cisplatin-induced apoptosis through NF-κB pathway.
201530
8 201524
9 201424
10 202121
11 201418
12 202215
13 201914
14 201512
15 202011
16 201711
17 202210
18 20189
19 20158
20 20218

About Muliang Ding

Muliang Ding is a scholar working on Molecular Biology, Cancer Research, Surgery, Epidemiology and Biomedical Engineering, having authored 29 papers that have together received 623 indexed citations. Recurring topics across this work include MicroRNA in disease regulation (6 papers), Circular RNAs in diseases (5 papers), Cancer-related molecular mechanisms research (4 papers), Osteoarthritis Treatment and Mechanisms (2 papers), Endoplasmic Reticulum Stress and Disease (2 papers), RNA Research and Splicing (2 papers), Extracellular vesicles in disease (2 papers) and Anatomy and Medical Technology (2 papers). The work is most often cited by research in Cancer Research (188 citations), Geriatrics and Gerontology (15 citations), Rehabilitation (28 citations), Molecular Biology (294 citations) and Epidemiology (124 citations). Muliang Ding has collaborated with scholars based in China, United States and Canada. Frequent co-authors include Deye Song, Jun Huang, Jiangdong Ni, Mingming Yan, Junjie Wang, Wenzhao Li, Ke Liu, Jiangdong Ni, Junjie Wang and Jianzhong Hu. Their work appears in journals such as Laboratory Investigation, Journal of Orthopaedic Surgery and Research, Bioactive Materials, Human Cell and BMC Surgery.

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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