Ranran Dai

657 citations
35 papers · 451 · h-index 12

Impact in

Papers in

Ranran Dai

33 papers receiving 447 citations

Peers

Ranran Dai
Comparison fields: 5 of 94
  • Pulmonary and Respiratory Medicine 125
  • Cancer Research 52
  • Genetics 33
  • Health Informatics 4
  • Emergency Medical Services 18
Replace Goh Tanaka with:
Goh Tanaka Japan
Yuqiong Yang China
Zhiwei Xu China
Colleen Smith United States
Lutz Welker Germany
D.Y. Wang Singapore
Xiaolin Yin China
Daisuke Kajiwara Japan
Ranran Dai relative to Goh Tanaka Japan Goh Tanaka's profile →
Citations per field
00.5×3.7×
Goh Tanaka · 1×
Citations per year

Countries citing papers authored by Ranran Dai

Since Specialization
Citations

This map shows the geographic impact of Ranran Dai'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 Ranran Dai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ranran Dai more than expected).

Fields of papers citing papers by Ranran Dai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ranran Dai. 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 Ranran Dai. The network helps show where Ranran Dai may publish in the future.

Co-authors

The 25 scholars most cited alongside Ranran Dai, 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 Ranran Dai Line = papers co-authored together Ranran Dai links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 35 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202053
2 202049
3 201646
4 201831
5 202127
6 202126
7 202223
8 202119
9 202219
10 202117
11
Delivery of adipose-derived mesenchymal stem cells attenuates airway responsiveness and inflammation in a mouse model of ovalbumin-induced asthma.
201717
12 201516
13 201211
14 201311
15 20209
16 20219
17 20218
18 20248
19 20188
20 20197

About Ranran Dai

Ranran Dai is a scholar working on Pulmonary and Respiratory Medicine, Molecular Biology, Cancer Research, Oncology and Physiology, having authored 35 papers that have together received 451 indexed citations. Recurring topics across this work include Chronic Obstructive Pulmonary Disease (COPD) Research (6 papers), Respiratory Support and Mechanisms (4 papers), Cancer-related molecular mechanisms research (4 papers), Circular RNAs in diseases (3 papers), Pediatric health and respiratory diseases (3 papers), RNA modifications and cancer (3 papers), Asthma and respiratory diseases (2 papers) and T-cell and B-cell Immunology (2 papers). The work is most often cited by research in Pulmonary and Respiratory Medicine (125 citations), Cancer Research (52 citations), Genetics (33 citations), Health Informatics (4 citations) and Emergency Medical Services (18 citations). Ranran Dai has collaborated with scholars based in China, United States and South Korea. Frequent co-authors include Guochao Shi, Yingmeng Ni, Wei Du, Yahui Liu, Guangtao Zhai, Menghan Hu, Wei Tang, Yaling Pan, Ping Wang and Lei Fan. Their work appears in journals such as Chronic Respiratory Disease, Saudi Journal of Biological Sciences, Tungsten, Cancer Management and Research and Clinical and Translational Allergy.

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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