Song-hua Wu
- Co-authors
- Weiping JiaKun‐san XiangTaishan ZhengHuijuan LuSuijun WangQingchuan ZhangCongrong WangBin Hong
- Topics
- Lipid metabolism and disorders (5 papers)Liver Disease Diagnosis and Treatment (4 papers)RNA modifications and cancer (4 papers)
- Partner nations
- ChinaSwedenUnited States
In The Last Decade
Song-hua Wu
27 papers receiving 445 citations
Peers
Comparison fields: 5 of 86
- Molecular Biology 202
- Epidemiology 112
- Endocrinology, Diabetes and Metabolism 109
- Genetics 96
- Surgery 75
Countries citing papers authored by Song-hua Wu
This map shows the geographic impact of Song-hua 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 Song-hua Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Song-hua Wu more than expected).
Fields of papers citing papers by Song-hua Wu
This network shows the impact of papers produced by Song-hua 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 Song-hua Wu. The network helps show where Song-hua Wu may publish in the future.
Co-authorship network of co-authors of Song-hua Wu
This figure shows the co-authorship network connecting the top 25 collaborators of Song-hua Wu. A scholar is included among the top collaborators of Song-hua 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 Song-hua Wu. Song-hua 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 | 36 | |
| 2 | 35 | |
| 3 | 19 | |
| 4 | [Detection rates of atherosclerosis by carotid versus lower limb ultrasonography in newly diagnosed type 2 diabetics]. | 1 |
| 5 | 16 | |
| 6 | 8 | |
| 7 | 36 | |
| 8 | 16 | |
| 9 | 1 | |
| 10 | 54 | |
| 11 | 22 | |
| 12 | 1 | |
| 13 | [Comparison of the application of three diagnostic criteria of metabolic syndrome in familial type 2 diabetic pedigrees]. | 3 |
| 14 | [Study on the status of metabolic syndrome in familial type 2 diabetes pedigrees]. | 1 |
| 15 | [Genetic characteristics of familial type 2 diabetes pedigrees: a preliminary analysis of 4468 persons from 715 pedigrees]. | 7 |
| 16 | 7 | |
| 17 | 2 | |
| 18 | [Mutation screening of GCK gene in Chinese early-onset diabetes population]. | 3 |
| 19 | 140 | |
| 20 | 3 |
About Song-hua Wu
Song-hua Wu is a scholar working on Endocrinology, Diabetes and Metabolism, Clinical Biochemistry and Cancer Research, having authored 27 papers that have together received 454 indexed citations. Recurring topics across this work include Lipid metabolism and disorders (5 papers), Liver Disease Diagnosis and Treatment (4 papers) and RNA modifications and cancer (4 papers). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (109 citations), Transportation (23 citations) and Genetics (96 citations). Song-hua Wu has collaborated with scholars based in China, Sweden and United States. Frequent co-authors include Weiping Jia, Kun‐san Xiang, Taishan Zheng, Huijuan Lu, Suijun Wang, Qingchuan Zhang, Congrong Wang, Bin Hong, Charlotte Ling and Rong Zhang. Their work appears in journals such as The Journal of Clinical Endocrinology & Metabolism, Diabetes and Gene.
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.