Li Nan

1.7k citations
45 papers · 1.1k · h-index 20

Impact in

  • Oncology top 10%
    • CAR-T cell therapy research
    • Cancer-related Molecular Pathways
  • Genetics top 10%
    • Virus-based gene therapy research

Papers in

Li Nan

43 papers receiving 1.1k citations

Peers

Li Nan
Comparison fields: 5 of 86
  • Oncology 352
  • Genetics 304
  • Molecular Biology 542
  • Immunology 158
  • Genetics 63
Replace Sabine M. Klauck with:
Sabine M. Klauck Germany
Ping He China
Fujun Li China
Baljinder Salh Canada
Xianping Lu China
Sharad Khare United States
Teresa G. Tessner United States
Sarah P. Short United States
Qinggao Zhang China
T Toge Japan
Li Nan relative to Sabine M. Klauck Germany Sabine M. Klauck's profile →
Citations per field
00.5×1.5×2.3×
Sabine M. Klauck · 1×
Citations per year

Countries citing papers authored by Li Nan

Since Specialization
Citations

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

Fields of papers citing papers by Li Nan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 45 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2005134
2
Antisense anti-MDM2 oligonucleotides as a novel therapeutic approach to human breast cancer: in vitro and in vivo activities and mechanisms.
200194
3 200585
4 201078
5 201866
6 201266
7 201058
8 201556
9 201545
10 200244
11 201339
12 201338
13 201936
14 201930
15 201429
16 201420
17 201720
18 200420
19 202219
20 200219

About Li Nan

Li Nan is a scholar working on Genetics, Molecular Biology, Oncology, Pharmacology and Epidemiology, having authored 45 papers that have together received 1.1k indexed citations. Recurring topics across this work include Virus-based gene therapy research (10 papers), Herpesvirus Infections and Treatments (5 papers), Inflammatory mediators and NSAID effects (5 papers), Multiple Myeloma Research and Treatments (4 papers), Bone health and treatments (4 papers), Phosphodiesterase function and regulation (3 papers), Proteoglycans and glycosaminoglycans research (3 papers) and Cancer-related Molecular Pathways (3 papers). The work is most often cited by research in Oncology (352 citations), Genetics (304 citations), Molecular Biology (542 citations), Immunology (158 citations) and Genetics (63 citations). Li Nan has collaborated with scholars based in United States, China and Egypt. Frequent co-authors include Sudhir Agrawal, Ruiwen Zhang, Gary A. Piazza, Adam B. Keeton, Dong Soo Yu, Bernard D. Gary, Elizabeth A. Beierle, Gregory K. Friedman, Huamiao Wang and James M. Markert. Their work appears in journals such as Blood, Cancer Research, Pediatric Research, Cancer Prevention Research and Neuro-Oncology.

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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