Xinglong Wang
- Molecular Biology top 0.5%
- Physiology top 0.2%
- Neurology top 0.5%
- Cellular and Molecular Neuroscience top 1%
- Neurology top 0.5%
- Co-authors
- Xiongwei ZhuGeorge PerryMark A. SmithBo SuHyoung‐gon LeeHisashi FujiokaWenzhang WangSandra L. Siedlak
- Topics
- Alzheimer's disease research and treatments (57 papers)Mitochondrial Function and Pathology (42 papers)Amyotrophic Lateral Sclerosis Research (18 papers)
- Journals
- Proceedings of the National Academy of SciencesNucleic Acids ResearchJournal of Biological Chemistry
- Partner nations
- United StatesChinaUnited Kingdom
In The Last Decade
Xinglong Wang
149 papers receiving 12.8k citations
Hit Papers
Peers
Comparison fields: 5 of 167
- Molecular Biology 7.3k
- Physiology 5.5k
- Neurology 2.2k
- Cellular and Molecular Neuroscience 1.9k
- Neurology 1.5k
Countries citing papers authored by Xinglong Wang
This map shows the geographic impact of Xinglong 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 Xinglong Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xinglong Wang more than expected).
Fields of papers citing papers by Xinglong Wang
This network shows the impact of papers produced by Xinglong 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 Xinglong Wang. The network helps show where Xinglong Wang may publish in the future.
Co-authorship network of co-authors of Xinglong Wang
This figure shows the co-authorship network connecting the top 25 collaborators of Xinglong Wang. A scholar is included among the top collaborators of Xinglong Wang 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 Xinglong Wang. Xinglong Wang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 1 | |
| 3 | 1 | |
| 4 | 3 | |
| 5 | 33 | |
| 6 | 1 | |
| 7 | 3 | |
| 8 | 25 | |
| 9 | 1 | |
| 10 | 308 | |
| 11 | 259 | |
| 12 | 47 | |
| 13 | 71 | |
| 14 | 52 | |
| 15 | 175 | |
| 16 | 67 | |
| 17 | 109 | |
| 18 | 147 | |
| 19 | Learning the Species of Biomedical Named Entities from Annotated Corpora | 10 |
| 20 | 122 |
About Xinglong Wang
Xinglong Wang is a scholar working on Biological Psychiatry, Physiology and Neurology, having authored 156 papers that have together received 13.0k indexed citations. Recurring topics across this work include Alzheimer's disease research and treatments (57 papers), Mitochondrial Function and Pathology (42 papers) and Amyotrophic Lateral Sclerosis Research (18 papers). The work is most often cited by research in Biological Psychiatry (728 citations), Physiology (5.5k citations) and Neurology (1.5k citations). Xinglong Wang has collaborated with scholars based in United States, China and United Kingdom. Frequent co-authors include Xiongwei Zhu, George Perry, Mark A. Smith, Bo Su, Hyoung‐gon Lee, Hisashi Fujioka, Wenzhang Wang, Sandra L. Siedlak, Paula I. Moreira and Gemma Casadesús. Their work appears in journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and Journal of Biological Chemistry.
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.