Song Wu

964 citations
34 papers · 625 · h-index 12

Impact in

Papers in

    • RNA modifications and cancer 4
    • Glycosylation and Glycoproteins Research 3
    • Biochemical and Structural Characterization 2
    • Cancer-related molecular mechanisms research 7
    • MicroRNA in disease regulation 3
    • Cancer Genomics and Diagnostics 2

Song Wu

33 papers receiving 604 citations

Peers

Song Wu
Comparison fields: 5 of 94
  • Complementary and alternative medicine 86
  • Pharmacology 86
  • Biotechnology 45
  • Aquatic Science 36
  • Molecular Biology 329
Replace Junyu Liu with:
Junyu Liu China
Kun Yeong Lee South Korea
Chao‐Neng Tseng Taiwan
Tae Hoon Lee South Korea
Yulong Chen China
Xue-Hai Jin Japan
Yu‐Yao Cao China
Miriam Zeini Spain
Tae-Kyu Park South Korea
Yuan-Jin Guo China
Song Wu relative to Junyu Liu China Junyu Liu's profile →
Citations per field
00.5×10×20×31×
Junyu Liu · 1×
Citations per year

Countries citing papers authored by Song Wu

Since Specialization
Citations

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

Fields of papers citing papers by Song Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 34 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2007162
2 200787
3 199956
4 199851
5 199833
6 200127
7 199927
8 202223
9 202222
10 202414
11 201812
12 202312
13 202311
14 199710
15 202210
16 20239
17 20227
18 20246
19 20256
20 20246

About Song Wu

Song Wu is a scholar working on Molecular Biology, Cancer Research, Pulmonary and Respiratory Medicine, Rheumatology and Complementary and alternative medicine, having authored 34 papers that have together received 625 indexed citations. Recurring topics across this work include Cancer-related molecular mechanisms research (7 papers), Osteoarthritis Treatment and Mechanisms (6 papers), Ferroptosis and cancer prognosis (6 papers), RNA modifications and cancer (4 papers), MicroRNA in disease regulation (3 papers), Glycosylation and Glycoproteins Research (3 papers), Cancer Genomics and Diagnostics (2 papers) and Biochemical and Structural Characterization (2 papers). The work is most often cited by research in Complementary and alternative medicine (86 citations), Pharmacology (86 citations), Biotechnology (45 citations), Aquatic Science (36 citations) and Molecular Biology (329 citations). Song Wu has collaborated with scholars based in China, South Korea and United States. Frequent co-authors include Yeong Shik Kim, Sung Ho Son, Heungsop Shin, Young Wan Ha, Lijia An, Qiao Su, Toshihiko Toida, Robert J. Linhardt, Bum-Soo Hahn and Junjie Huang. Their work appears in journals such as Frontiers in Oncology, Archives of Pharmacal Research, Thrombosis Research, Journal of Orthopaedic Translation and Chemical Engineering Journal.

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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