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Subclass Mapping: Identifying Common Subtypes in Independent Disease Data Sets
Whole genome expression profiles are widely used to discover molecular subtypes of diseases. A remaining challenge is to identify the correspondence or commonality of subtypes found in multiple, independent data sets generated on various platforms. While model-based supervised learning is often used...
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| 主要な著者: | , , , , |
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| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
Public Library of Science
2007
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| 主題: | |
| オンライン･アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC2065909/ https://ncbi.nlm.nih.gov/pubmed/18030330 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pone.0001195 |
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