Minghua Wu
- Molecular Biology top 5%
- Pathology and Forensic Medicine top 1%
- Pulmonary and Respiratory Medicine top 5%
- Immunology top 5%
- Cancer Research top 5%
- Co-authors
- John VargaShervin AssassiMaureen D. MayesSandeep K. AgarwalCarol Feghali‐BostwickSwati BhattacharyyaDenisa S. MelichianAsish K. Ghosh
- Topics
- Systemic Sclerosis and Related Diseases (32 papers)Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis (10 papers)Dermatologic Treatments and Research (6 papers)
- Partner nations
- United StatesChinaUnited Kingdom
In The Last Decade
Minghua Wu
56 papers receiving 3.1k citations
Peers
Comparison fields: 5 of 126
- Molecular Biology 1.4k
- Pathology and Forensic Medicine 1.1k
- Pulmonary and Respiratory Medicine 689
- Immunology 555
- Cancer Research 544
Countries citing papers authored by Minghua Wu
This map shows the geographic impact of Minghua Wu'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 Minghua Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Minghua Wu more than expected).
Fields of papers citing papers by Minghua Wu
This network shows the impact of papers produced by Minghua Wu. 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 Minghua Wu. The network helps show where Minghua Wu may publish in the future.
Co-authorship network of co-authors of Minghua Wu
This figure shows the co-authorship network connecting the top 25 collaborators of Minghua Wu. A scholar is included among the top collaborators of Minghua Wu based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Minghua Wu. Minghua Wu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 7 | |
| 3 | 39 | |
| 4 | 17 | |
| 5 | 15 | |
| 6 | Geniposide inhibited endothelial-mesenchymal transition via the mTOR signaling pathway in a bleomycin-induced scleroderma mouse model. | 29 |
| 7 | 32 | |
| 8 | 11 | |
| 9 | 17 | |
| 10 | 74 | |
| 11 | 79 | |
| 12 | 104 | |
| 13 | 67 | |
| 14 | 193 | |
| 15 | 47 | |
| 16 | 67 | |
| 17 | [Functional genomics of nasopharyngeal carcinoma susceptibility/suppressor gene]. | 2 |
| 18 | 36 | |
| 19 | 26 | |
| 20 | 49 |
About Minghua Wu
Minghua Wu is a scholar working on Pathology and Forensic Medicine, Dermatology and Cancer Research, having authored 59 papers that have together received 3.1k indexed citations. Recurring topics across this work include Systemic Sclerosis and Related Diseases (32 papers), Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis (10 papers) and Dermatologic Treatments and Research (6 papers). The work is most often cited by research in Pathology and Forensic Medicine (1.1k citations), Dermatology (373 citations) and Cancer Research (544 citations). Minghua Wu has collaborated with scholars based in United States, China and United Kingdom. Frequent co-authors include John Varga, Shervin Assassi, Maureen D. Mayes, Sandeep K. Agarwal, Carol Feghali‐Bostwick, Swati Bhattacharyya, Denisa S. Melichian, Asish K. Ghosh, Filemon K. Tan and Eric T. Chang. Their work appears in journals such as Nature Communications, The Journal of Experimental Medicine 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.