Can Yang
Impact in
- Genetics top 2%
- Genetic Associations and Epidemiology
- Genetic Mapping and Diversity in Plants and Animals
- Genetic and phenotypic traits in livestock
- Molecular Biology top 10%
- Bioinformatics and Genomic Networks
- Gene expression and cancer classification
- Single-cell and spatial transcriptomics
- Machine Learning in Bioinformatics
Papers in
- Genetics 38
- Genetic Associations and Epidemiology 38
- Genetic Mapping and Diversity in Plants and Animals 16
- Genetic and phenotypic traits in livestock 12
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- Bioinformatics and Genomic Networks 11
- Single-cell and spatial transcriptomics 9
- Gene expression and cancer classification 9
- Epigenetics and DNA Methylation 5
Can Yang
66 papers receiving 1.8k citations
Peers
Comparison fields: 5 of 138
- Genetics 1.1k
- Molecular Biology 1.0k
- Statistics and Probability 74
- Cancer Research 109
- Computational Mathematics 4
Countries citing papers authored by Can Yang
This map shows the geographic impact of Can Yang'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 Can Yang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Can Yang more than expected).
Fields of papers citing papers by Can Yang
This network shows the impact of papers produced by Can Yang. 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 Can Yang. The network helps show where Can Yang may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Can Yang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 0 | |
| 2 | 2025 | 0 | |
| 3 | 2025 | 18 | |
| 4 | 2024 | 2 | |
| 5 | 2024 | 13 | |
| 6 | 2023 | 1 | |
| 7 | 2023 | 64 | |
| 8 | 2023 | 0 | |
| 9 | 2022 | 8 | |
| 10 | 2021 | 1 | |
| 11 | 2020 | 33 | |
| 12 | 2020 | 20 | |
| 13 | 2020 | 12 | |
| 14 | 2020 | 2 | |
| 15 | 2019 | 9 | |
| 16 | 2019 | 26 | |
| 17 | 2019 | 15 | |
| 18 | On the Convergence of the EM Algorithm: From the Statistical Perspective | 2016 | 2 |
| 19 | 2011 | 9 | |
| 20 | 2009 | 62 |
About Can Yang
Can Yang is a scholar working on Genetics, Molecular Biology, Biophysics, Statistics and Probability and Spectroscopy, having authored 76 papers that have together received 1.8k indexed citations. Recurring topics across this work include Genetic Associations and Epidemiology (38 papers), Genetic Mapping and Diversity in Plants and Animals (16 papers), Genetic and phenotypic traits in livestock (12 papers), Bioinformatics and Genomic Networks (11 papers), Single-cell and spatial transcriptomics (9 papers), Gene expression and cancer classification (9 papers), Liver Disease Diagnosis and Treatment (6 papers) and Epigenetics and DNA Methylation (5 papers). The work is most often cited by research in Genetics (1.1k citations), Molecular Biology (1.0k citations), Statistics and Probability (74 citations), Cancer Research (109 citations) and Computational Mathematics (4 citations). Can Yang has collaborated with scholars based in Hong Kong, China and Singapore. Frequent co-authors include Xiang Wan, Weichuan Yu, Qiang Yang, Hong Xue, Nelson L.S. Tang, Jin Liu, Xiaodan Fan, Xianghong Hu, Jia Zhao and Zengyou He. Their work appears in journals such as Bioinformatics, Nature Communications, BMC Bioinformatics, The American Journal of Human Genetics and NAR Genomics and Bioinformatics.
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.