A Method for the Structure-Based, Genome-Wide Analysis of Bacterial Intergenic Sequences Identifies Shared Compositional and Functional Features

In this paper, we propose a computational strategy for performing genome-wide analyses of intergenic sequences in bacterial genomes. Following similar directions of a previous paper, where a method for genome-wide analysis of eucaryotic Intergenic sequences was proposed, here we developed a tool for...

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Autores principales: Lenzini, Leonardo, Di Patti, Francesca, Livi, Roberto, Fondi, Marco, Fani, Renato, Mengoni, Alessio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6826451/
https://www.ncbi.nlm.nih.gov/pubmed/31652625
http://dx.doi.org/10.3390/genes10100834
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author Lenzini, Leonardo
Di Patti, Francesca
Livi, Roberto
Fondi, Marco
Fani, Renato
Mengoni, Alessio
author_facet Lenzini, Leonardo
Di Patti, Francesca
Livi, Roberto
Fondi, Marco
Fani, Renato
Mengoni, Alessio
author_sort Lenzini, Leonardo
collection PubMed
description In this paper, we propose a computational strategy for performing genome-wide analyses of intergenic sequences in bacterial genomes. Following similar directions of a previous paper, where a method for genome-wide analysis of eucaryotic Intergenic sequences was proposed, here we developed a tool for implementing similar concepts in bacteria genomes. This allows us to (i) classify intergenic sequences into clusters, characterized by specific global structural features and (ii) draw possible relations with their functional features.
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spelling pubmed-68264512019-11-18 A Method for the Structure-Based, Genome-Wide Analysis of Bacterial Intergenic Sequences Identifies Shared Compositional and Functional Features Lenzini, Leonardo Di Patti, Francesca Livi, Roberto Fondi, Marco Fani, Renato Mengoni, Alessio Genes (Basel) Article In this paper, we propose a computational strategy for performing genome-wide analyses of intergenic sequences in bacterial genomes. Following similar directions of a previous paper, where a method for genome-wide analysis of eucaryotic Intergenic sequences was proposed, here we developed a tool for implementing similar concepts in bacteria genomes. This allows us to (i) classify intergenic sequences into clusters, characterized by specific global structural features and (ii) draw possible relations with their functional features. MDPI 2019-10-22 /pmc/articles/PMC6826451/ /pubmed/31652625 http://dx.doi.org/10.3390/genes10100834 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Lenzini, Leonardo
Di Patti, Francesca
Livi, Roberto
Fondi, Marco
Fani, Renato
Mengoni, Alessio
A Method for the Structure-Based, Genome-Wide Analysis of Bacterial Intergenic Sequences Identifies Shared Compositional and Functional Features
title A Method for the Structure-Based, Genome-Wide Analysis of Bacterial Intergenic Sequences Identifies Shared Compositional and Functional Features
title_full A Method for the Structure-Based, Genome-Wide Analysis of Bacterial Intergenic Sequences Identifies Shared Compositional and Functional Features
title_fullStr A Method for the Structure-Based, Genome-Wide Analysis of Bacterial Intergenic Sequences Identifies Shared Compositional and Functional Features
title_full_unstemmed A Method for the Structure-Based, Genome-Wide Analysis of Bacterial Intergenic Sequences Identifies Shared Compositional and Functional Features
title_short A Method for the Structure-Based, Genome-Wide Analysis of Bacterial Intergenic Sequences Identifies Shared Compositional and Functional Features
title_sort method for the structure-based, genome-wide analysis of bacterial intergenic sequences identifies shared compositional and functional features
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6826451/
https://www.ncbi.nlm.nih.gov/pubmed/31652625
http://dx.doi.org/10.3390/genes10100834
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