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LifeStyle-Specific-Islands (LiSSI): Integrated Bioinformatics Platform for Genomic Island Analysis

Distinct bacteria are able to cope with highly diverse lifestyles; for instance, they can be free living or host-associated. Thus, these organisms must possess a large and varied genomic arsenal to withstand different environmental conditions. To facilitate the identification of genomic features tha...

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Detalles Bibliográficos
Autores principales: Barbosa, Eudes, Röttger, Richard, Hauschild, Anne-Christin, de Castro Soares, Siomar, Böcker, Sebastian, Azevedo, Vasco, Baumbach, Jan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: De Gruyter 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6042826/
https://www.ncbi.nlm.nih.gov/pubmed/28678736
http://dx.doi.org/10.1515/jib-2017-0010
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author Barbosa, Eudes
Röttger, Richard
Hauschild, Anne-Christin
de Castro Soares, Siomar
Böcker, Sebastian
Azevedo, Vasco
Baumbach, Jan
author_facet Barbosa, Eudes
Röttger, Richard
Hauschild, Anne-Christin
de Castro Soares, Siomar
Böcker, Sebastian
Azevedo, Vasco
Baumbach, Jan
author_sort Barbosa, Eudes
collection PubMed
description Distinct bacteria are able to cope with highly diverse lifestyles; for instance, they can be free living or host-associated. Thus, these organisms must possess a large and varied genomic arsenal to withstand different environmental conditions. To facilitate the identification of genomic features that might influence bacterial adaptation to a specific niche, we introduce LifeStyle-Specific-Islands (LiSSI). LiSSI combines evolutionary sequence analysis with statistical learning (Random Forest with feature selection, model tuning and robustness analysis). In summary, our strategy aims to identify conserved consecutive homology sequences (islands) in genomes and to identify the most discriminant islands for each lifestyle.
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spelling pubmed-60428262019-01-28 LifeStyle-Specific-Islands (LiSSI): Integrated Bioinformatics Platform for Genomic Island Analysis Barbosa, Eudes Röttger, Richard Hauschild, Anne-Christin de Castro Soares, Siomar Böcker, Sebastian Azevedo, Vasco Baumbach, Jan J Integr Bioinform Research Articles Distinct bacteria are able to cope with highly diverse lifestyles; for instance, they can be free living or host-associated. Thus, these organisms must possess a large and varied genomic arsenal to withstand different environmental conditions. To facilitate the identification of genomic features that might influence bacterial adaptation to a specific niche, we introduce LifeStyle-Specific-Islands (LiSSI). LiSSI combines evolutionary sequence analysis with statistical learning (Random Forest with feature selection, model tuning and robustness analysis). In summary, our strategy aims to identify conserved consecutive homology sequences (islands) in genomes and to identify the most discriminant islands for each lifestyle. De Gruyter 2017-07-05 /pmc/articles/PMC6042826/ /pubmed/28678736 http://dx.doi.org/10.1515/jib-2017-0010 Text en ©2017, Eudes Barbosa et al., published by De Gruyter, Berlin/Boston http://creativecommons.org/licenses/by-nc-nd/3.0 This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.
spellingShingle Research Articles
Barbosa, Eudes
Röttger, Richard
Hauschild, Anne-Christin
de Castro Soares, Siomar
Böcker, Sebastian
Azevedo, Vasco
Baumbach, Jan
LifeStyle-Specific-Islands (LiSSI): Integrated Bioinformatics Platform for Genomic Island Analysis
title LifeStyle-Specific-Islands (LiSSI): Integrated Bioinformatics Platform for Genomic Island Analysis
title_full LifeStyle-Specific-Islands (LiSSI): Integrated Bioinformatics Platform for Genomic Island Analysis
title_fullStr LifeStyle-Specific-Islands (LiSSI): Integrated Bioinformatics Platform for Genomic Island Analysis
title_full_unstemmed LifeStyle-Specific-Islands (LiSSI): Integrated Bioinformatics Platform for Genomic Island Analysis
title_short LifeStyle-Specific-Islands (LiSSI): Integrated Bioinformatics Platform for Genomic Island Analysis
title_sort lifestyle-specific-islands (lissi): integrated bioinformatics platform for genomic island analysis
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6042826/
https://www.ncbi.nlm.nih.gov/pubmed/28678736
http://dx.doi.org/10.1515/jib-2017-0010
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