Li Nan

1.7k citations
44 papers · 1.1k indexed · h-index 19

Impact in

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

Papers in

    • RNA modifications and cancer 3
    • Bone health and treatments 4
    • Cancer-related Molecular Pathways 3

Li Nan

43 papers receiving 1.1k citations

Peers

Li Nan
Comparison fields: 5 of 89
  • Oncology 375
  • Genetics 300
  • Molecular Biology 566
  • Immunology 166
  • Genetics 72
Replace Sabine M. Klauck with:
Sabine M. Klauck Germany
Fujun Li China
Adel Kardosh United States
Ki Beom Bae South Korea
Sarah P. Short United States
Songbai Lin United States
Teresa G. Tessner United States
Xianping Lu China
Parthasarathy Chandrakesan United States
Chao‐Wen Cheng Taiwan
Li Nan relative to Sabine M. Klauck Germany Sabine M. Klauck's profile →
Citations per field
00.5×1.5×2.2×
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 44 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2005122
2
Antisense anti-MDM2 oligonucleotides as a novel therapeutic approach to human breast cancer: in vitro and in vivo activities and mechanisms.
200191
3 200581
4 201076
5 201265
6 201859
7 201056
8 201554
9 201545
10 200241
11 201338
12 201336
13 201935
14 201429
15 201929
16 201420
17 200419
18 200219
19 202218
20 201718

About Li Nan

Li Nan is a scholar working on Molecular Biology, Oncology, Genetics, Epidemiology and Pharmacology, having authored 44 papers that have together received 1.1k indexed citations. Recurring topics across this work include Virus-based gene therapy research (11 papers), Herpesvirus Infections and Treatments (7 papers), Multiple Myeloma Research and Treatments (5 papers), Inflammatory mediators and NSAID effects (5 papers), Cytomegalovirus and herpesvirus research (4 papers), Bone health and treatments (4 papers), Cancer-related Molecular Pathways (3 papers) and RNA modifications and cancer (3 papers). The work is most often cited by research in Oncology (375 citations), Genetics (300 citations), Molecular Biology (566 citations), Immunology (166 citations) and Genetics (72 citations). Li Nan has collaborated with scholars based in United States, China and Egypt. Frequent co-authors include Sudhir Agrawal, Gary A. Piazza, Adam B. Keeton, Ruiwen Zhang, Dong Soo Yu, Bernard D. Gary, Elizabeth A. Beierle, Huamiao Wang, James M. Markert and G. Yancey Gillespie. Their work appears in journals such as Neuro-Oncology, Cancer Research, Cancer Prevention Research, Pediatric Research and Blood.

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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