Jun Tang

2.3k citations
87 papers · 1.1k · h-index 20

Impact in

Papers in

Jun Tang

77 papers receiving 1.1k citations

Peers

Jun Tang
Comparison fields: 5 of 125
  • Pediatrics, Perinatology and Child Health 213
  • Obstetrics and Gynecology 68
  • Developmental Neuroscience 38
  • Nutrition and Dietetics 98
  • Critical Care and Intensive Care Medicine 25
Replace I-Chun Lin with:
I-Chun Lin Taiwan
Leyla Cinel Türkiye
Salvatore Pellegrino Italy
Mehmet Aksoy Türkiye
Kajal Jain India
Fang Gao Smith United Kingdom
Shaowen Tang China
Luc Lorgis France
Szabolcs Várbı́ró Hungary
Jun Tang relative to I-Chun Lin Taiwan I-Chun Lin's profile →
Citations per field
00.5×2.7×
I-Chun Lin · 1×
Citations per year

Countries citing papers authored by Jun Tang

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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.

Border = papers with Jun Tang Line = papers co-authored together Jun Tang links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 87 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201863
2 202062
3 202160
4 201058
5 201957
6 202151
7 201244
8 201641
9 200939
10 201538
11 201935
12 201634
13 202133
14 201728
15 201826
16 201126
17 201824
18 202421
19 202021
20 201920

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 (213 citations), Obstetrics and Gynecology (68 citations), Developmental Neuroscience (38 citations), Nutrition and Dietetics (98 citations) and Critical Care and Intensive Care Medicine (25 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, Haoran Wang, Meng Mao and Dapeng Chen. Their work appears in journals such as BMJ Open, BMC Pediatrics, Journal of Evidence-Based Medicine, Reviews in the Neurosciences and Medicine.

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.

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