Laijun Song

1.0k citations
49 papers · 711 · h-index 18

Impact in

    • MicroRNA in disease regulation
    • Cancer-related molecular mechanisms research
  • Genetics top 10%
    • Mesenchymal stem cell research
    • Glioma Diagnosis and Treatment

Papers in

Laijun Song

46 papers receiving 696 citations

Peers

Laijun Song
Comparison fields: 5 of 97
  • Cancer Research 154
  • Genetics 92
  • Neurology 97
  • Internal Medicine 23
  • Pharmacology 34
Replace Xin Deng with:
Xin Deng China
Yulia Kiyan Germany
Chuan Wen China
Md Sanaullah Sajib United States
Tiecheng Yu China
Sven Danckwardt Germany
Naadiya Carrim Canada
Peng Chen China
Laijun Song relative to Xin Deng China Xin Deng's profile →
Citations per field
00.5×3.4×
Xin Deng · 1×
Citations per year

Countries citing papers authored by Laijun Song

Since Specialization
Citations

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

Fields of papers citing papers by Laijun Song

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 49 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200751
2 201545
3 201144
4 201240
5 201638
6 201633
7 201333
8 201526
9 201324
10 200723
11 201522
12 201322
13 201622
14 202119
15 201218
16 201218
17 201718
18 201717
19 201117
20 201917

About Laijun Song

Laijun Song is a scholar working on Cancer Research, Molecular Biology, Genetics, Neurology and Epidemiology, having authored 49 papers that have together received 711 indexed citations. Recurring topics across this work include Glioma Diagnosis and Treatment (9 papers), MicroRNA in disease regulation (6 papers), Meningioma and schwannoma management (4 papers), Pituitary Gland Disorders and Treatments (4 papers), Spinal Dysraphism and Malformations (4 papers), Neuroblastoma Research and Treatments (4 papers), Cancer-related molecular mechanisms research (4 papers) and Cancer, Hypoxia, and Metabolism (4 papers). The work is most often cited by research in Cancer Research (154 citations), Genetics (92 citations), Neurology (97 citations), Internal Medicine (23 citations) and Pharmacology (34 citations). Laijun Song has collaborated with scholars based in China, United States and Malaysia. Frequent co-authors include Fuyou Guo, Bo Yang, Yongli Lou, Xinbin Guo, Bo Yang, Xiang Hu, Fangxia Guan, Xinting Wei, Hui Zhang and Xianzhi Liu. Their work appears in journals such as Journal of Stroke and Cerebrovascular Diseases, Clinical Neurology and Neurosurgery, Neurological Sciences, Journal of Biochemical and Molecular Toxicology and Saudi Journal of Biological Sciences.

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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