Fang Li

6.1k citations
146 papers · 4.4k indexed · 1 hit paper · h-index 30
    • Cancer-related molecular mechanisms research 51
    • MicroRNA in disease regulation 28
    • NF-κB Signaling Pathways 7
    • Cancer, Hypoxia, and Metabolism 6
    • Circular RNAs in diseases 18
    • RNA Research and Splicing 16
    • RNA modifications and cancer 15
  • Oncology top 5%
  • Nephrology top 5%
  • Immunology top 5%
    • Cervical Cancer and HPV Research 12

Fang Li

140 papers receiving 4.4k citations

Hit Papers

Caspase 3–mediated stimulation of tumor cell repopulation...7062011202620162021200400600

Peers

Fang Li
Comparison fields: 5 of 150
  • Cancer Research 1.6k
  • Molecular Biology 2.4k
  • Oncology 815
  • Nephrology 181
  • Immunology 516
Replace Yin Wang with:
Yin Wang China
Johannes Grillari Austria
Zhen Chen China
Lin Chen China
Wei Cui China
Je‐Yoel Cho South Korea
Sean E. Gill Canada
Hui‐Yun Wang China
Masaki Inada Japan
Yuying Liu China
Fang Li relative to Yin Wang China Yin Wang's profile →
Citations per field
00.5×1.5×
Yin Wang · 1×
Citations per year

Countries citing papers authored by Fang Li

Since Specialization
Citations

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

Fields of papers citing papers by Fang Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20250
2 20250
3 20250
4 20251
5 20250
6 20247
7 202318
8 20237
9 20233
10 20226
11 2020111
12 201911
13 2019177
14 201220
15 201128
16
DNA polymorphism of introns 1 and 2 of prolactin receptor gene and its association with litter size in goats.
201113
17 201048
18 2007358
19 2006131
20
Study on RBP4 as a Candidate Gene for Prolificacy of Small Tailed Han Sheep
20061

About Fang Li

Fang Li is a scholar working on Cancer Research, Horticulture and Molecular Biology, having authored 146 papers that have together received 4.4k indexed citations. Recurring topics across this work include Cancer-related molecular mechanisms research (51 papers), MicroRNA in disease regulation (28 papers), Circular RNAs in diseases (18 papers), RNA Research and Splicing (16 papers), RNA modifications and cancer (15 papers), Cervical Cancer and HPV Research (12 papers), NF-κB Signaling Pathways (7 papers) and Cancer, Hypoxia, and Metabolism (6 papers). The work is most often cited by research in Cancer Research (1.6k citations), Molecular Biology (2.4k citations) and Oncology (815 citations). Fang Li has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Chuan‐Yuan Li, Qian Huang, Mark W. Dewhirst, Zahid N. Rabbani, Bin Yan, Wenrong Li, Željko Vujašković, Shanling Liu, Xinjian Liu and Pierre Sonveaux. Their work appears in journals such as Journal of Biological Chemistry, Cancer Research, Frontiers in Genetics, Journal of Constructional Steel Research and Cellular Signalling.

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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