Weichen Song
Impact in
- Biological Psychiatry top 10%
- Tryptophan and brain disorders
- Biophysics top 10%
- Cell Image Analysis Techniques
Papers in
-
- Bioinformatics and Genomic Networks 6
- Single-cell and spatial transcriptomics 5
- Epigenetics and DNA Methylation 3
- Genetics 10
- Genetic Associations and Epidemiology 7
- Co-authors
- Guan Ning Lin (27 shared papers)Shunying Yu (12 shared papers)Brandon Wong (1 shared paper)Ting Zhang (1 shared paper)Xiao Liu (1 shared paper)Xianting Ding (1 shared paper)Weidi Wang (11 shared papers)Juju Miao (3 shared papers)
- Journals
- Genes (3 papers)Cell & Bioscience (2 papers)Genomics (2 papers)BMC Medical Genomics (2 papers)Research (2 papers)
- Partner nations
- ChinaUnited StatesAustralia
In The Last Decade
Weichen Song
37 papers receiving 517 citations
Peers
Comparison fields: 5 of 101
- Biological Psychiatry 30
- Biophysics 39
- Cancer Research 51
- Molecular Biology 236
- Behavioral Neuroscience 10
Countries citing papers authored by Weichen Song
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
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.
All Works
Showing the 20 most-cited of 40 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 110 | |
| 2 | 2021 | 84 | |
| 3 | 2021 | 27 | |
| 4 | 2020 | 26 | |
| 5 | 2020 | 24 | |
| 6 | 2021 | 22 | |
| 7 | 2021 | 21 | |
| 8 | 2022 | 18 | |
| 9 | 2019 | 17 | |
| 10 | 2024 | 17 | |
| 11 | 2021 | 14 | |
| 12 | 2022 | 13 | |
| 13 | 2023 | 12 | |
| 14 | 2021 | 12 | |
| 15 | 2023 | 10 | |
| 16 | 2019 | 9 | |
| 17 | 2021 | 9 | |
| 18 | 2023 | 8 | |
| 19 | 2022 | 7 | |
| 20 | 2019 | 6 |
About Weichen Song
Weichen Song is a scholar working on Molecular Biology, Genetics, Cellular and Molecular Neuroscience, Electrical and Electronic Engineering and Cancer Research, having authored 40 papers that have together received 519 indexed citations. Recurring topics across this work include Genetic Associations and Epidemiology (7 papers), Bioinformatics and Genomic Networks (6 papers), Single-cell and spatial transcriptomics (5 papers), Epigenetics and DNA Methylation (3 papers), Advanced Memory and Neural Computing (2 papers), Obsessive-Compulsive Spectrum Disorders (2 papers), Bladder and Urothelial Cancer Treatments (2 papers) and Autism Spectrum Disorder Research (2 papers). The work is most often cited by research in Biological Psychiatry (30 citations), Biophysics (39 citations), Cancer Research (51 citations), Molecular Biology (236 citations) and Behavioral Neuroscience (10 citations). Weichen Song has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Guan Ning Lin, Shunying Yu, Brandon Wong, Ting Zhang, Xiao Liu, Xianting Ding, Weidi Wang, Juju Miao, Man Zhang and Xiaomu Cheng. Their work appears in journals such as Genes, Cell & Bioscience, Genomics, BMC Medical Genomics and Research.
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.