Jun Tang
Impact in
-
- Neonatal and fetal brain pathology
- Birth, Development, and Health
- Infant Development and Preterm Care
- Developmental Neuroscience top 10%
Papers in
-
- Neonatal and fetal brain pathology 11
- Neonatal Health and Biochemistry 4
-
- Neonatal Respiratory Health Research 12
- Co-authors
- Dezhi Mu (50 shared papers)Yi Qu (32 shared papers)Tao Xiong (19 shared papers)Jing Shi (12 shared papers)Li Zhang (8 shared papers)Fengyan Zhao (8 shared papers)Tingting Zhu (6 shared papers)Dapeng Chen (2 shared papers)
- Journals
- BMJ Open (4 papers)BMC Pediatrics (3 papers)Medicine (2 papers)Scientific Reports (2 papers)Reviews in the Neurosciences (2 papers)
- Partner nations
- ChinaUnited StatesUnited Kingdom
In The Last Decade
Jun Tang
77 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 126
- Pediatrics, Perinatology and Child Health 217
- Developmental Neuroscience 39
- Obstetrics and Gynecology 68
- Nutrition and Dietetics 101
- Critical Care and Intensive Care Medicine 26
Countries citing papers authored by Jun Tang
This map shows the geographic impact of Jun 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 Jun Tang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jun Tang more than expected).
Fields of papers citing papers by Jun Tang
This network shows the impact of papers produced by Jun 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 Jun Tang. The network helps show where Jun Tang may publish in the future.
Co-authors
The 25 scholars most cited alongside Jun 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
Showing the 20 most-cited of 87 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 65 | |
| 2 | 2020 | 63 | |
| 3 | 2021 | 60 | |
| 4 | 2010 | 58 | |
| 5 | 2019 | 57 | |
| 6 | 2021 | 52 | |
| 7 | 2012 | 44 | |
| 8 | 2016 | 42 | |
| 9 | 2009 | 40 | |
| 10 | 2015 | 38 | |
| 11 | 2019 | 36 | |
| 12 | 2016 | 36 | |
| 13 | 2021 | 34 | |
| 14 | 2017 | 29 | |
| 15 | 2011 | 27 | |
| 16 | 2018 | 26 | |
| 17 | 2018 | 25 | |
| 18 | 2024 | 21 | |
| 19 | 2017 | 21 | |
| 20 | 2020 | 21 |
About Jun Tang
Jun Tang is a scholar working on Pediatrics, Perinatology and Child Health, Pulmonary and Respiratory Medicine, Public Health, Environmental and Occupational Health, Surgery and Epidemiology, having authored 87 papers that have together received 1.1k indexed citations. Recurring topics across this work include Neonatal Respiratory Health Research (12 papers), Neonatal and fetal brain pathology (11 papers), Pregnancy and preeclampsia studies (4 papers), Infant Nutrition and Health (4 papers), Neonatal Health and Biochemistry (4 papers), Maternal Mental Health During Pregnancy and Postpartum (3 papers), Congenital Diaphragmatic Hernia Studies (3 papers) and Axon Guidance and Neuronal Signaling (3 papers). The work is most often cited by research in Pediatrics, Perinatology and Child Health (217 citations), Developmental Neuroscience (39 citations), Obstetrics and Gynecology (68 citations), Nutrition and Dietetics (101 citations) and Critical Care and Intensive Care Medicine (26 citations). Jun Tang has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Dezhi Mu, Yi Qu, Tao Xiong, Jing Shi, Li Zhang, Fengyan Zhao, Tingting Zhu, Dapeng Chen, Haoran Wang and Meng Mao. Their work appears in journals such as BMJ Open, BMC Pediatrics, Medicine, Scientific Reports and Reviews in the Neurosciences.
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.