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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Detalles Bibliográficos
Autores principales: Wang, Yin, Li, Rudong, Zhou, Yuhua, Ling, Zongxin, Guo, Xiaokui, Xie, Lu, Liu, Lei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2016
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4769744/
https://www.ncbi.nlm.nih.gov/pubmed/27057545
http://dx.doi.org/10.1155/2016/6598307

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4769744/
https://www.ncbi.nlm.nih.gov/pubmed/27057545
http://dx.doi.org/10.1155/2016/6598307

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