Weichen Song

1.2k citations
39 papers · 483 · h-index 12

Impact in

Papers in

    • Bioinformatics and Genomic Networks 10
    • Single-cell and spatial transcriptomics 7
    • Epigenetics and DNA Methylation 4
    • RNA Research and Splicing 3
    • Gene expression and cancer classification 3
    • Genetic Associations and Epidemiology 9

Weichen Song

37 papers receiving 480 citations

Peers

Weichen Song
Comparison fields: 5 of 102
  • Biological Psychiatry 32
  • Biophysics 43
  • Behavioral Neuroscience 15
  • Cancer Research 61
  • Molecular Biology 257
Replace Neethu Michael with:
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Nikhil Rao China
Changchun Chen United Kingdom
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Saba Shahin United States
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Weichen Song relative to Neethu Michael United States Neethu Michael's profile →
Citations per field
00.5×3.8×
Neethu Michael · 1×
Citations per year

Countries citing papers authored by Weichen Song

Since Specialization
Citations

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

Fields of papers citing papers by Weichen Song

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 39 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2019108
2 202178
3 202126
4 202024
5 202024
6 202121
7 202120
8 201917
9 202113
10 202212
11 202212
12 202111
13 202411
14 202310
15 20199
16 20239
17 20218
18 20238
19 20227
20 20196

About Weichen Song

Weichen Song is a scholar working on Molecular Biology, Genetics, Cellular and Molecular Neuroscience, Neurology and Cancer Research, having authored 39 papers that have together received 483 indexed citations. Recurring topics across this work include Bioinformatics and Genomic Networks (10 papers), Genetic Associations and Epidemiology (9 papers), Single-cell and spatial transcriptomics (7 papers), Neuroinflammation and Neurodegeneration Mechanisms (4 papers), Epigenetics and DNA Methylation (4 papers), Tryptophan and brain disorders (3 papers), RNA Research and Splicing (3 papers) and Gene expression and cancer classification (3 papers). The work is most often cited by research in Biological Psychiatry (32 citations), Biophysics (43 citations), Behavioral Neuroscience (15 citations), Cancer Research (61 citations) and Molecular Biology (257 citations). Weichen Song has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Guan Ning Lin, Shunying Yu, Ting Zhang, Brandon Wong, Xianting Ding, Xiao Liu, Wei Qian, Weidi Wang, Jia Wang and Wenqin Luo. Their work appears in journals such as Genes, Psychiatry Research, Genomics, BMC Medical Genomics and Remote Sensing.

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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