Fanglong Wu

39 papers receiving 1.4k citations

Hit Papers

TGF-β signaling in the tumor metabolic microenvironment and targeted therapies 2022 · 150 citations
1500+1+3Years since publication100200300400500

Peers

Fanglong Wu
Comparison fields: 5 of 106
  • Cancer Research 411
  • Otorhinolaryngology 92
  • Oncology 529
  • Immunology 303
  • Molecular Biology 607
Replace Koroku Kato with:
Koroku Kato Japan
Eri Sasabe Japan
Yunong Wu China
Maria Nyström Sweden
Yong Fu China
Dongmiao Wang China
Christina Springstead Scanlon United States
Fengcai Wei China
Laikui Liu China
Richard J. Bauer Germany
Fanglong Wu relative to Koroku Kato Japan Koroku Kato's profile →
Citations per field
00.5×7.7×
Koroku Kato · 1×
Citations per year

Countries citing papers authored by Fanglong Wu

Since Specialization
Citations

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

Fields of papers citing papers by Fanglong Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 42 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Signaling pathways in cancer-associated fibroblasts and targeted therapy for cancer
Hit paper breakdown →
2021501
2
TGF-β signaling in the tumor metabolic microenvironment and targeted therapies
Hit paper breakdown →
2022150
3 2020138
4 202170
5 201758
6 202049
7 201544
8 201938
9 201932
10 201831
11 201430
12 201827
13 202327
14 202126
15 201821
16 202219
17 201919
18 201519
19 202216
20 201810

About Fanglong Wu

Fanglong Wu is a scholar working on Molecular Biology, Oncology, Cancer Research, Surgery and Otorhinolaryngology, having authored 42 papers that have together received 1.4k indexed citations. Recurring topics across this work include Head and Neck Cancer Studies (7 papers), Salivary Gland Tumors Diagnosis and Treatment (6 papers), Oral health in cancer treatment (5 papers), Cancer, Hypoxia, and Metabolism (5 papers), Oral Health Pathology and Treatment (5 papers), Cancer Cells and Metastasis (4 papers), Immune cells in cancer (4 papers) and Autoimmune Bullous Skin Diseases (4 papers). The work is most often cited by research in Cancer Research (411 citations), Otorhinolaryngology (92 citations), Oncology (529 citations), Immunology (303 citations) and Molecular Biology (607 citations). Fanglong Wu has collaborated with scholars based in China, United States and Russia. Frequent co-authors include Hongmei Zhou, Jin Yang, Junjiang Liu, Qingxiang Zeng, Jingtian Mu, Ye Wang, Xueke Shi, Xiao‐Jing Wang, Qinghong Gao and Kelsey Weigel. Their work appears in journals such as Cochrane Database of Systematic Reviews, Oral Diseases, International Journal of Oral Science, Journal of Oral Pathology and Medicine and European Journal of Neurology.

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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