Lan Dong

1.5k citations
9 papers · 1.0k · 1 hit paper · h-index 6

Impact in

Papers in

Lan Dong

9 papers receiving 966 citations

Lan Dong's Hit Papers

Possible Vertical Transmission of SARS-CoV-2 From an Infected Mother to Her Newborn 2020 · 840 citations
8400+2+4Years since publication250500750

Peers

Lan Dong
Comparison fields: 5 of 67
  • Obstetrics and Gynecology 806
  • Infectious Diseases 220
  • Public Health, Environmental and Occupational Health 343
  • Pediatrics, Perinatology and Child Health 230
  • Oncology 162
Replace Marwa O. Elgendy with:
Marwa O. Elgendy Egypt
Jianping Zhang China
Kristine E. Shields United States
Ozlem Equils United States
Ida Laake Norway
Mohammad Hossein Panahi Iran
Paola Meraviglia Italy
Belinda J. Njiro Tanzania
Margarida Tavares Portugal
Julianna Schantz-Dunn United States
Lan Dong relative to Marwa O. Elgendy Egypt Marwa O. Elgendy's profile →
Citations per field
00.5×10×15×18.3×
Marwa O. Elgendy · 1×
Citations per year

Countries citing papers authored by Lan Dong

Since Specialization
Citations

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

Fields of papers citing papers by Lan Dong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

9 of 9 papers shown
#Work
1
Possible Vertical Transmission of SARS-CoV-2 From an Infected Mother to Her Newborn
Hit paper breakdown →
2020840
2 202054
3 202049
4 202028
5 202016
6 202011
7 20164
8 20243
9
Mesenchymal stem cell-derived exosomes ameliorate TGF-β1-induced endometrial fibrosis by altering their miRNA profile.
20232

About Lan Dong

Lan Dong is a scholar working on Obstetrics and Gynecology, Infectious Diseases, Oncology, Public Health, Environmental and Occupational Health and Immunology, having authored 9 papers that have together received 1.0k indexed citations. Recurring topics across this work include COVID-19 Impact on Reproduction (3 papers), Reproductive System and Pregnancy (2 papers), COVID-19 and healthcare impacts (2 papers), COVID-19 Clinical Research Studies (2 papers), Digital Imaging for Blood Diseases (1 paper), COVID-19 diagnosis using AI (1 paper), MicroRNA in disease regulation (1 paper) and Endometriosis Research and Treatment (1 paper). The work is most often cited by research in Obstetrics and Gynecology (806 citations), Infectious Diseases (220 citations), Public Health, Environmental and Occupational Health (343 citations), Pediatrics, Perinatology and Child Health (230 citations) and Oncology (162 citations). Lan Dong has collaborated with scholars based in China, Australia and Canada. Frequent co-authors include Jing Yang, Jinhua Tian, Songming He, Chen Liu, Jian Wang, Lian Yang, Dayi Chen, Cheng Peng, Xiaoqi Pan and Lu Zhang. Their work appears in journals such as Virus Research, JAMA, BMC Pregnancy and Childbirth, Journal of Cellular and Molecular Medicine and Microscopy Research and Technique.

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.

Explore authors with similar magnitude of impact