Yinghao Wang

97 papers receiving 1.5k citations

Yinghao Wang's Hit Papers

Gene mining and genomics-assisted breeding empowered by the pangenome of tea plant Camellia sinensis 2023 · 94 citations
940+1+2Years since publication255075

Peers

Yinghao Wang
Comparison fields: 5 of 135
  • Aging 63
  • Catalysis 64
  • Cancer Research 123
  • Biological Psychiatry 19
  • Pathology and Forensic Medicine 130
Replace Tianpeng Zhang with:
Tianpeng Zhang China
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Citations per year

Countries citing papers authored by Yinghao Wang

Since Specialization
Citations

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

Fields of papers citing papers by Yinghao Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 108 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2016149
2 2018146
3
Gene mining and genomics-assisted breeding empowered by the pangenome of tea plant Camellia sinensis
Hit paper breakdown →
202394
4 202059
5 202258
6 201954
7 202053
8 202049
9 201744
10 202141
11 202141
12 201940
13 202036
14 201835
15
Long non-coding RNA LINC00673 promotes breast cancer proliferation and metastasis through regulating B7-H6 and epithelial-mesenchymal transition.
201834
16 202032
17 201829
18 201727
19 202025
20 201923

About Yinghao Wang

Yinghao Wang is a scholar working on Analytical Chemistry, Mechanics of Materials, Pathology and Forensic Medicine, Spectroscopy and Biomedical Engineering, having authored 108 papers that have together received 1.6k indexed citations. Recurring topics across this work include Mass Spectrometry Techniques and Applications (8 papers), Petroleum Processing and Analysis (7 papers), Catalysis for Biomass Conversion (7 papers), Advanced Photocatalysis Techniques (6 papers), Analytical Chemistry and Chromatography (5 papers), Nanomaterials for catalytic reactions (5 papers), Catalysis and Hydrodesulfurization Studies (5 papers) and Catalytic Processes in Materials Science (5 papers). The work is most often cited by research in Aging (63 citations), Catalysis (64 citations), Cancer Research (123 citations), Biological Psychiatry (19 citations) and Pathology and Forensic Medicine (130 citations). Yinghao Wang has collaborated with scholars based in China, United States and France. Frequent co-authors include Qiue Cao, Wenhao Fang, Ling Wang, Jun Quan, Yongxing Wang, Yehua Han, Ouchen Wang, Adheesh Bhandari, Fang Li and Meng Zhang. Their work appears in journals such as Analytical and Bioanalytical Chemistry, Chemical Communications, Molecular Catalysis, Horticulture Research and Journal of Separation Science.

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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