Xiaolu Tang
- Infectious Diseases top 2%
- SARS-CoV-2 and COVID-19 Research 9
- Viral gastroenteritis research and epidemiology 4
- Modeling and Simulation top 2%
- COVID-19 epidemiological studies 3
- Behavioral Neuroscience top 5%
- Stress Responses and Cortisol 6
- Animal Science and Zoology top 5%
- Animal Virus Infections Studies 5
- Biochemistry top 5%
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- Hormonal Regulation and Hypertension 4
- Adrenal Hormones and Disorders 3
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- Estrogen and related hormone effects 3
- Co-authors
- Jian LüXinkai WuYuange DuanYirong WangChangcheng WuHong ZhangZhaohui QianXiang Li
- Journals
- Nucleic Acids Research (1 paper)Nature Communications (2 papers)SHILAP Revista de lepidopterología (1 paper)
- Partner nations
- ChinaAustraliaUnited States
In The Last Decade
Xiaolu Tang
36 papers receiving 1.8k citations
Hit Papers
Peers
Comparison fields: 5 of 130
- Infectious Diseases 933
- Modeling and Simulation 172
- Behavioral Neuroscience 78
- Animal Science and Zoology 161
- Biochemistry 83
Countries citing papers authored by Xiaolu Tang
This map shows the geographic impact of Xiaolu Tang'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 Xiaolu Tang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiaolu Tang more than expected).
Fields of papers citing papers by Xiaolu Tang
This network shows the impact of papers produced by Xiaolu Tang. 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 Xiaolu Tang. The network helps show where Xiaolu Tang may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Xiaolu Tang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2024 | 18 | |
| 2 | 2023 | 13 | |
| 3 | 2023 | 12 | |
| 4 | 2023 | 20 | |
| 5 | 2022 | 13 | |
| 6 | 2021 | 13 | |
| 7 | 2021 | 60 | |
| 8 | 2021 | 2 | |
| 9 | 2020 | 16 | |
| 10 | On the origin and continuing evolution of SARS-CoV-2breakdown → | 2020 | 1071 |
| 11 | COVID-19 Screening and Triage Using a Unified Approach to the Management of Relevant Healthcare Workers, Procedure and Goals within a Regional Medical Consortium: a Development from Disorderly to Orderly | 2020 | 1 |
| 12 | 2020 | 3 | |
| 13 | 2016 | 87 | |
| 14 | 2016 | 12 | |
| 15 | 2015 | 39 | |
| 16 | 2015 | 13 | |
| 17 | 2011 | 13 | |
| 18 | 2010 | 13 | |
| 19 | 2006 | 35 | |
| 20 | 2006 | 38 |
About Xiaolu Tang
Xiaolu Tang is a scholar working on Behavioral Neuroscience, Modeling and Simulation and Animal Science and Zoology, having authored 36 papers that have together received 1.9k indexed citations. Recurring topics across this work include SARS-CoV-2 and COVID-19 Research (9 papers), Stress Responses and Cortisol (6 papers), Animal Virus Infections Studies (5 papers), Viral gastroenteritis research and epidemiology (4 papers), Hormonal Regulation and Hypertension (4 papers), COVID-19 epidemiological studies (3 papers), Estrogen and related hormone effects (3 papers) and Adrenal Hormones and Disorders (3 papers). The work is most often cited by research in Infectious Diseases (933 citations), Modeling and Simulation (172 citations) and Behavioral Neuroscience (78 citations). Xiaolu Tang has collaborated with scholars based in China, Australia and United States. Frequent co-authors include Jian Lü, Xinkai Wu, Yuange Duan, Yirong Wang, Changcheng Wu, Hong Zhang, Zhaohui Qian, Xiang Li, Jie Cui and Yuhe Song. Their work appears in journals such as Nucleic Acids Research, Nature Communications and SHILAP Revista de lepidopterología.
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.