Li Wan

7.4k citations
298 papers · 5.6k · h-index 39

Impact in

    • Cancer-related molecular mechanisms research
    • MicroRNA in disease regulation
    • Circular RNAs in diseases
    • RNA modifications and cancer
    • RNA Research and Splicing

Papers in

    • Bioinformatics and Genomic Networks 31
    • RNA modifications and cancer 22
    • Gene expression and cancer classification 12
    • Cancer-related molecular mechanisms research 28
    • MicroRNA in disease regulation 13

Li Wan

278 papers receiving 5.5k citations

Peers

Li Wan
Comparison fields: 5 of 186
  • Cancer Research 1.3k
  • Molecular Biology 2.3k
  • Catalysis 200
  • Molecular Medicine 97
  • Immunology 373
Replace Yang Chen with:
Yang Chen China
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Li Wan relative to Yang Chen China Yang Chen's profile →
Citations per field
00.5×1.5×2.3×
Yang Chen · 1×
Citations per year

Countries citing papers authored by Li Wan

Since Specialization
Citations

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

Fields of papers citing papers by Li Wan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 298 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2017325
2 2015277
3 2016190
4 2015162
5 2016130
6 2018118
7 2010103
8 2021101
9 201898
10 202097
11 201996
12 201789
13 201382
14 201482
15 201372
16 202171
17 201357
18 201855
19 201254
20 201053

About Li Wan

Li Wan is a scholar working on Molecular Biology, Cancer Research, Epidemiology, Pulmonary and Respiratory Medicine and Infectious Diseases, having authored 298 papers that have together received 5.6k indexed citations. Recurring topics across this work include Bioinformatics and Genomic Networks (31 papers), Cancer-related molecular mechanisms research (28 papers), RNA modifications and cancer (22 papers), Computational Drug Discovery Methods (14 papers), Tuberculosis Research and Epidemiology (13 papers), MicroRNA in disease regulation (13 papers), Gene expression and cancer classification (12 papers) and Ferroptosis and cancer prognosis (11 papers). The work is most often cited by research in Cancer Research (1.3k citations), Molecular Biology (2.3k citations), Catalysis (200 citations), Molecular Medicine (97 citations) and Immunology (373 citations). Li Wan has collaborated with scholars based in China, United States and Canada. Frequent co-authors include Ming Sun, Zhao-xia Wang, Tongpeng Xu, Erbao Zhang, Rong Kong, Guanhua Du, Liam John France, Qing Yang, Xuehui Li and Liwen Ren. Their work appears in journals such as PLoS ONE, Scientific Reports, Molecular BioSystems, International Journal of Molecular Medicine and Frontiers in Genetics.

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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