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Motif-Based Text Mining of Microbial Metagenome Redundancy Profiling Data for Disease Classification
Background. Text data of 16S rRNA are informative for classifications of microbiota-associated diseases. However, the raw text data need to be systematically processed so that features for classification can be defined/extracted; moreover, the high-dimension feature spaces generated by the text data...
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| 出版年: | Biomed Res Int |
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| 主要な著者: | , , , , , , |
| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
Hindawi Publishing Corporation
2016
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| 主題: | |
| オンライン･アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4769744/ https://ncbi.nlm.nih.gov/pubmed/27057545 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1155/2016/6598307 |
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