Xiaoli Gao
- Molecular Biology
- Plant Science
- Health, Toxicology and Mutagenesis top 10%
- Artificial Intelligence
- Computer Vision and Pattern Recognition
- Co-authors
- John WithersWeiqing ZengAlexandre BrutusA. Daniel JonesSheng Yang HeDang-xia ZhouJames M. KremerHai‐Xu Wang
- Topics
- Melamine detection and toxicity (4 papers)Mercury impact and mitigation studies (4 papers)CAR-T cell therapy research (3 papers)
- Partner nations
- ChinaUnited StatesTaiwan
In The Last Decade
Xiaoli Gao
32 papers receiving 422 citations
Peers
Comparison fields: 5 of 95
- Molecular Biology 115
- Plant Science 109
- Health, Toxicology and Mutagenesis 78
- Artificial Intelligence 55
- Computer Vision and Pattern Recognition 44
Countries citing papers authored by Xiaoli Gao
This map shows the geographic impact of Xiaoli Gao'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 Xiaoli Gao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiaoli Gao more than expected).
Fields of papers citing papers by Xiaoli Gao
This network shows the impact of papers produced by Xiaoli Gao. 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 Xiaoli Gao. The network helps show where Xiaoli Gao may publish in the future.
Co-authorship network of co-authors of Xiaoli Gao
This figure shows the co-authorship network connecting the top 25 collaborators of Xiaoli Gao. A scholar is included among the top collaborators of Xiaoli Gao 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 Xiaoli Gao. Xiaoli Gao 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 | 0 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | 3 | |
| 6 | 5 | |
| 7 | 3 | |
| 8 | 5 | |
| 9 | 43 | |
| 10 | 3 | |
| 11 | 5 | |
| 12 | 19 | |
| 13 | 6 | |
| 14 | 27 | |
| 15 | 8 | |
| 16 | 113 | |
| 17 | 71 | |
| 18 | [Inhibitory effect of sinomenine on H2O2-induced apoptosis in neonatal rat cardiomyocytes]. | 14 |
| 19 | [Effect of total flaveos of Gymostemma pentaphyllum on protein expression of Fas/FasL genes and TNF-alpha concentration in cultured neonatal rat cardiomyocytes with hypoxia-reoxygenation]. | 3 |
| 20 | 11 |
About Xiaoli Gao
Xiaoli Gao is a scholar working on Horticulture, Health, Toxicology and Mutagenesis and Toxicology, having authored 35 papers that have together received 436 indexed citations. Recurring topics across this work include Melamine detection and toxicity (4 papers), Mercury impact and mitigation studies (4 papers) and CAR-T cell therapy research (3 papers). The work is most often cited by research in Health, Toxicology and Mutagenesis (78 citations), Plant Science (109 citations) and Media Technology (24 citations). Xiaoli Gao has collaborated with scholars based in China, United States and Taiwan. Frequent co-authors include John Withers, Weiqing Zeng, Alexandre Brutus, A. Daniel Jones, Sheng Yang He, Dang-xia Zhou, James M. Kremer, Hai‐Xu Wang, Youli Zheng and Min Dong. Their work appears in journals such as Blood, The Journal of Immunology and IEEE Transactions on Geoscience and Remote Sensing.
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.