Liyang Wang

3.6k citations
89 papers · 2.5k indexed · h-index 30

Impact in

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

Papers in

Liyang Wang

88 papers receiving 2.5k citations

Peers

Liyang Wang
Comparison fields: 5 of 165
  • Cancer Research 352
  • Oncology 540
  • Orthopedics and Sports Medicine 170
  • Immunology 372
  • Molecular Biology 978
Replace Masato Maeda with:
Masato Maeda Japan
Salvatore Campo Italy
Marco Prunotto Switzerland
Hao Chen China
Kouichi Ozaki Japan
Xiaofeng Chen China
Qing Zhao China
Isabella Ellinger Austria
Tuo Zhang United States
Xiaobo Zhou United States
Liyang Wang relative to Masato Maeda Japan Masato Maeda's profile →
Citations per field
00.5×
Masato Maeda · 1×
Citations per year

Countries citing papers authored by Liyang Wang

Since Specialization
Citations

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

Fields of papers citing papers by Liyang Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 202511
2 20251
3 20252
4 20251
5 20243
6 202411
7 20235
8 20237
9 20232
10 20239
11 202213
12 202111
13 202133
14 20206
15 202038
16 201536
17 2012104
18 2006149
19 200531
20 200053

About Liyang Wang

Liyang Wang is a scholar working on Cancer Research, Oncology, Rheumatology, Aging and Radiology, Nuclear Medicine and Imaging, having authored 89 papers that have together received 2.5k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (6 papers), Herpesvirus Infections and Treatments (5 papers), Bone Metabolism and Diseases (5 papers), Autophagy in Disease and Therapy (5 papers), Machine Learning in Bioinformatics (4 papers), Ginseng Biological Effects and Applications (4 papers), Radiomics and Machine Learning in Medical Imaging (4 papers) and AI in cancer detection (4 papers). The work is most often cited by research in Cancer Research (352 citations), Oncology (540 citations), Orthopedics and Sports Medicine (170 citations), Immunology (372 citations) and Molecular Biology (978 citations). Liyang Wang has collaborated with scholars based in China, United States and Japan. Frequent co-authors include Yukio Yoneda, Eiichi Hinoi, Harvey M. Friedman, John M. Lubinski, Toshiyuki Yoneda, Toru Hiraga, Sayumi Fujimori, Kyosuke Uno, John D. Lambris and Liuyang Zhao. Their work appears in journals such as Journal of Virology, Scientific Reports, Foods, Cancers and The Journal of Immunology.

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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