Xiaojuan Wang
Impact in
Papers in
- Genetics 25
- Genetic diversity and population structure 8
- Genetic and phenotypic traits in livestock 5
- Forensic and Genetic Research 3
- Virus-based gene therapy research 3
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- Genomics and Phylogenetic Studies 3
- Molecular Biology Techniques and Applications 3
- Co-authors
- Michaël Wink (10 shared papers)Sonja Krstin (5 shared papers)Herbenya Peixoto (7 shared papers)Mariana Roxo (4 shared papers)E. Charles Brummer (1 shared paper)Xuehui Li (1 shared paper)Yanling Wei (1 shared paper)Yongshuai Sun (3 shared papers)
- Journals
- Molecules (3 papers)Frontiers in Plant Science (2 papers)Molecular Ecology (2 papers)PLoS ONE (2 papers)Poultry Science (1 paper)
- Partner nations
- ChinaGermanyUnited States
In The Last Decade
Xiaojuan Wang
41 papers receiving 797 citations
Peers
Comparison fields: 5 of 102
- Aging 38
- Genetics 240
- Biochemistry 37
- Drug Discovery 1
- Molecular Biology 358
Countries citing papers authored by Xiaojuan Wang
This map shows the geographic impact of Xiaojuan 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 Xiaojuan Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiaojuan Wang more than expected).
Fields of papers citing papers by Xiaojuan Wang
This network shows the impact of papers produced by Xiaojuan 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 Xiaojuan Wang. The network helps show where Xiaojuan Wang may publish in the future.
Co-authors
The 25 scholars most cited alongside Xiaojuan Wang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 44 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 102 | |
| 2 | 2010 | 88 | |
| 3 | 2004 | 50 | |
| 4 | 2011 | 48 | |
| 5 | 2017 | 41 | |
| 6 | 2017 | 35 | |
| 7 | 2016 | 35 | |
| 8 | Clinicopathological significance of fragile histidine triad transcription protein expression in breast carcinoma. | 2001 | 27 |
| 9 | 2017 | 26 | |
| 10 | 2016 | 26 | |
| 11 | 2016 | 26 | |
| 12 | 2020 | 23 | |
| 13 | 2018 | 23 | |
| 14 | 2016 | 21 | |
| 15 | 2018 | 20 | |
| 16 | 2018 | 20 | |
| 17 | 2011 | 20 | |
| 18 | 2019 | 18 | |
| 19 | 2019 | 17 | |
| 20 | 2015 | 15 |
About Xiaojuan Wang
Xiaojuan Wang is a scholar working on Genetics, Molecular Biology, Plant Science, Ecology, Evolution, Behavior and Systematics and Cell Biology, having authored 44 papers that have together received 803 indexed citations. Recurring topics across this work include Genetic diversity and population structure (8 papers), Genetic and phenotypic traits in livestock (5 papers), Cancer Treatment and Pharmacology (3 papers), Forensic and Genetic Research (3 papers), Genomics and Phylogenetic Studies (3 papers), Virus-based gene therapy research (3 papers), Microtubule and mitosis dynamics (3 papers) and Molecular Biology Techniques and Applications (3 papers). The work is most often cited by research in Aging (38 citations), Genetics (240 citations), Biochemistry (37 citations), Drug Discovery (1 citation) and Molecular Biology (358 citations). Xiaojuan Wang has collaborated with scholars based in China, Germany and United States. Frequent co-authors include Michaël Wink, Sonja Krstin, Herbenya Peixoto, Mariana Roxo, E. Charles Brummer, Xuehui Li, Yanling Wei, Yongshuai Sun, Diane Gesty‐Palmer and Michihisa Umetani. Their work appears in journals such as Molecules, Frontiers in Plant Science, Molecular Ecology, PLoS ONE and Poultry 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.