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Cancer classification and pathway discovery using nonnegative matrix factorization
OBJECTIVES: Extracting genetic information from a full range of sequencing data is important for understanding disease. We propose a novel method to effectively explore the landscape of genetic mutations and aggregate them to predict cancer type. DESIGN: We applied non-smooth non-negative matrix fac...
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| 出版年: | J Biomed Inform |
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| 主要な著者: | , , , , , |
| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
2019
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| 主題: | |
| オンライン･アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6697569/ https://ncbi.nlm.nih.gov/pubmed/31271844 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.jbi.2019.103247 |
| タグ: |
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