An analysis of non-cultivable bacteria using WEKA

The study of metagenomics from high throughput sequencing data processed through Waikato Environment for Knowledge Analysis (WEKA) is gaining momentum in recent years. Therefore, we report an analysis of metagenome data generated using T-RFLP followed by using the SMO (Sequential minimal optimizatio...

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Detalles Bibliográficos
Autores principales: Patil, Pritee Chunarkar, Panchal, Pradnya Suresh, Madiwale, Shweta, Tale, Vidya Sunil
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Biomedical Informatics 2020
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7649025/
https://www.ncbi.nlm.nih.gov/pubmed/33214750
http://dx.doi.org/10.6026/97320630016620
Descripción
Sumario:The study of metagenomics from high throughput sequencing data processed through Waikato Environment for Knowledge Analysis (WEKA) is gaining momentum in recent years. Therefore, we report an analysis of metagenome data generated using T-RFLP followed by using the SMO (Sequential minimal optimization) algorithm in WEKA to identify the total amount of cultured and uncultured microorganism present in the sample collected from multiple sources.

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