Xiaoyan Ming

522 citations
17 papers · 360 · h-index 9

Impact in

Papers in

    • Melanoma and MAPK Pathways 2
    • DNA Repair Mechanisms 1
    • Pluripotent Stem Cells Research 1
    • Cancer-related Molecular Pathways 2

Xiaoyan Ming

16 papers receiving 357 citations

Peers

Xiaoyan Ming
Comparison fields: 5 of 77
  • Cancer Research 68
  • Health, Toxicology and Mutagenesis 65
  • Hepatology 18
  • Molecular Biology 168
  • Transplantation 6
Replace Kun‐Chieh Chen with:
Kun‐Chieh Chen Taiwan
Yubo Shi China
Zhipeng Pan China
Lesly Doníz-Padilla Mexico
Tommaso Cavalleri Italy
Yasutomo Suzuki Japan
C-L Yu Taiwan
Jiansi Chen China
Xiaoyan Ming relative to Kun‐Chieh Chen Taiwan Kun‐Chieh Chen's profile →
Citations per field
00.5×2.6×
Kun‐Chieh Chen · 1×
Citations per year

Countries citing papers authored by Xiaoyan Ming

Since Specialization
Citations

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

Fields of papers citing papers by Xiaoyan Ming

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

17 of 17 papers shown
#Work
1 201073
2 201773
3 201344
4 201236
5 201625
6 202025
7
Long non-coding RNA NEAT1 predicts elevated chronic obstructive pulmonary disease (COPD) susceptibility and acute exacerbation risk, and correlates with higher disease severity, inflammation, and lower miR-193a in COPD patients.
201922
8 201021
9 202019
10 20207
11 20186
12 20244
13 20142
14 20251
15 20091
16 20221
17
Application of Nutritional Risk Screening 2002,Mini Nutritional Assessment,and clinical laboratory measurements in nutrition survey of hospitalized elderly patients
20160

About Xiaoyan Ming

Xiaoyan Ming is a scholar working on Molecular Biology, Oncology, Cancer Research, Physiology and Health, Toxicology and Mutagenesis, having authored 17 papers that have together received 360 indexed citations. Recurring topics across this work include Cancer-related Molecular Pathways (2 papers), Air Quality and Health Impacts (2 papers), Cellular Mechanics and Interactions (2 papers), Melanoma and MAPK Pathways (2 papers), Cancer-related molecular mechanisms research (2 papers), DNA Repair Mechanisms (1 paper), Pluripotent Stem Cells Research (1 paper) and Inflammatory mediators and NSAID effects (1 paper). The work is most often cited by research in Cancer Research (68 citations), Health, Toxicology and Mutagenesis (65 citations), Hepatology (18 citations), Molecular Biology (168 citations) and Transplantation (6 citations). Xiaoyan Ming has collaborated with scholars based in China, Hong Kong and United States. Frequent co-authors include Peng Deng, Yong Jiang, Xiaowei Gong, Chung Mau Lo, Xiao Qi Wang, Wei Yi, Sheung Tat Fan, Yun Zhou, Xiuqing Cui and Weihong Chen. Their work appears in journals such as Biological and Pharmaceutical Bulletin, Hepatology, Environmental Pollution, BMC Developmental Biology and PLoS ONE.

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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