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Clustering on Human Microbiome Sequencing Data: A Distance-Based Unsupervised Learning Model
Modeling and analyzing human microbiome allows the assessment of the microbial community and its impacts on human health. Microbiome composition can be quantified using 16S rRNA technology into sequencing data, which are usually skewed and heavy-tailed with excess zeros. Clustering methods are usefu...
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| 出版年: | Microorganisms |
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| 主要な著者: | , |
| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
MDPI
2020
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| 主題: | |
| オンライン･アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7589204/ https://ncbi.nlm.nih.gov/pubmed/33092203 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3390/microorganisms8101612 |
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