Lan Rong

36 papers receiving 1.0k citations

Lan Rong's Hit Papers

Computational screening of antagonists against the SARS-CoV-2 (COVID-19) coronavirus by molecular docking 2020 · 227 citations
2270+2+4Years since publication50100150200

Peers

Lan Rong
Comparison fields: 5 of 113
  • Gastroenterology 56
  • Pharmacology 78
  • Biochemistry 48
  • Complementary and alternative medicine 49
  • Computational Theory and Mathematics 110
Replace Matilde Merino‐Sanjuán with:
Matilde Merino‐Sanjuán Spain
Suneela Dhaneshwar India
Manoj Kumar India
Xinan Wu China
Bor‐Ru Lin Taiwan
Miriam Verwei Netherlands
Quanpeng Li China
Xianxiu Ge China
Isamu Murata Japan
Lan Rong relative to Matilde Merino‐Sanjuán Spain Matilde Merino‐Sanjuán's profile →
Citations per field
00.5×2×3×4.1×
Matilde Merino‐Sanjuán · 1×
Citations per year

Countries citing papers authored by Lan Rong

Since Specialization
Citations

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

Fields of papers citing papers by Lan Rong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 36 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Computational screening of antagonists against the SARS-CoV-2 (COVID-19) coronavirus by molecular docking
Hit paper breakdown →
2020227
2 2010159
3 201991
4 201074
5 202162
6 202156
7 201346
8 202131
9 201826
10 201826
11 201324
12 201523
13 201521
14 202020
15 201720
16 201217
17 201616
18 202115
19 202013
20 202212

About Lan Rong

Lan Rong is a scholar working on Molecular Biology, Surgery, Biomaterials, Pharmacology and Genetics, having authored 36 papers that have together received 1.1k indexed citations. Recurring topics across this work include Inflammatory Bowel Disease (5 papers), Natural product bioactivities and synthesis (5 papers), Helicobacter pylori-related gastroenterology studies (4 papers), Phytochemistry and Bioactive Compounds (4 papers), Phytochemical Studies and Bioactivities (3 papers), Pharmacological Effects of Natural Compounds (3 papers), Antibiotics Pharmacokinetics and Efficacy (2 papers) and Gut microbiota and health (2 papers). The work is most often cited by research in Gastroenterology (56 citations), Pharmacology (78 citations), Biochemistry (48 citations), Complementary and alternative medicine (49 citations) and Computational Theory and Mathematics (110 citations). Lan Rong has collaborated with scholars based in China and United States. Frequent co-authors include Ran Yu, Rong Shen, Peng Li, Chen Liang, Yichang Yu, Bing Wang, Liang Zhong, Yibin Jiang, Zhining Xia and Liang Zhong. Their work appears in journals such as Journal of Asian Natural Products Research, International Journal of Environmental Research and Public Health, Environmental Toxicology and Pharmacology, Chinese Chemical Letters and Magnetic Resonance in Chemistry.

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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