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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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
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author Patil, Pritee Chunarkar
Panchal, Pradnya Suresh
Madiwale, Shweta
Tale, Vidya Sunil
author_facet Patil, Pritee Chunarkar
Panchal, Pradnya Suresh
Madiwale, Shweta
Tale, Vidya Sunil
author_sort Patil, Pritee Chunarkar
collection PubMed
description 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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spelling pubmed-76490252020-11-18 An analysis of non-cultivable bacteria using WEKA Patil, Pritee Chunarkar Panchal, Pradnya Suresh Madiwale, Shweta Tale, Vidya Sunil Bioinformation Research Article 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. Biomedical Informatics 2020-08-31 /pmc/articles/PMC7649025/ /pubmed/33214750 http://dx.doi.org/10.6026/97320630016620 Text en © 2020 Biomedical Informatics http://creativecommons.org/licenses/by/3.0/ This is an Open Access article which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. This is distributed under the terms of the Creative Commons Attribution License.
spellingShingle Research Article
Patil, Pritee Chunarkar
Panchal, Pradnya Suresh
Madiwale, Shweta
Tale, Vidya Sunil
An analysis of non-cultivable bacteria using WEKA
title An analysis of non-cultivable bacteria using WEKA
title_full An analysis of non-cultivable bacteria using WEKA
title_fullStr An analysis of non-cultivable bacteria using WEKA
title_full_unstemmed An analysis of non-cultivable bacteria using WEKA
title_short An analysis of non-cultivable bacteria using WEKA
title_sort analysis of non-cultivable bacteria using weka
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7649025/
https://www.ncbi.nlm.nih.gov/pubmed/33214750
http://dx.doi.org/10.6026/97320630016620
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