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Orphelia: predicting genes in metagenomic sequencing reads

Metagenomic sequencing projects yield numerous sequencing reads of a diverse range of uncultivated and mostly yet unknown microorganisms. In many cases, these sequencing reads cannot be assembled into longer contigs. Thus, gene prediction tools that were originally developed for whole-genome analysi...

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Detalles Bibliográficos
Autores principales: Hoff, Katharina J., Lingner, Thomas, Meinicke, Peter, Tech, Maike
Formato: Texto
Lenguaje:English
Publicado: Oxford University Press 2009
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2703946/
https://www.ncbi.nlm.nih.gov/pubmed/19429689
http://dx.doi.org/10.1093/nar/gkp327
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author Hoff, Katharina J.
Lingner, Thomas
Meinicke, Peter
Tech, Maike
author_facet Hoff, Katharina J.
Lingner, Thomas
Meinicke, Peter
Tech, Maike
author_sort Hoff, Katharina J.
collection PubMed
description Metagenomic sequencing projects yield numerous sequencing reads of a diverse range of uncultivated and mostly yet unknown microorganisms. In many cases, these sequencing reads cannot be assembled into longer contigs. Thus, gene prediction tools that were originally developed for whole-genome analysis are not suitable for processing metagenomes. Orphelia is a program for predicting genes in short DNA sequences that is available through a web server application (http://orphelia.gobics.de). Orphelia utilizes prediction models that were created with machine learning techniques on the basis of a wide range of annotated genomes. In contrast to other methods for metagenomic gene prediction, Orphelia has fragment length-specific prediction models for the two most popular sequencing techniques in metagenomics, chain termination sequencing and pyrosequencing. These models ensure highly specific gene predictions.
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spelling pubmed-27039462009-07-01 Orphelia: predicting genes in metagenomic sequencing reads Hoff, Katharina J. Lingner, Thomas Meinicke, Peter Tech, Maike Nucleic Acids Res Articles Metagenomic sequencing projects yield numerous sequencing reads of a diverse range of uncultivated and mostly yet unknown microorganisms. In many cases, these sequencing reads cannot be assembled into longer contigs. Thus, gene prediction tools that were originally developed for whole-genome analysis are not suitable for processing metagenomes. Orphelia is a program for predicting genes in short DNA sequences that is available through a web server application (http://orphelia.gobics.de). Orphelia utilizes prediction models that were created with machine learning techniques on the basis of a wide range of annotated genomes. In contrast to other methods for metagenomic gene prediction, Orphelia has fragment length-specific prediction models for the two most popular sequencing techniques in metagenomics, chain termination sequencing and pyrosequencing. These models ensure highly specific gene predictions. Oxford University Press 2009-07-01 2009-05-08 /pmc/articles/PMC2703946/ /pubmed/19429689 http://dx.doi.org/10.1093/nar/gkp327 Text en © 2009 The Author(s) http://creativecommons.org/licenses/by-nc/2.0/uk/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Articles
Hoff, Katharina J.
Lingner, Thomas
Meinicke, Peter
Tech, Maike
Orphelia: predicting genes in metagenomic sequencing reads
title Orphelia: predicting genes in metagenomic sequencing reads
title_full Orphelia: predicting genes in metagenomic sequencing reads
title_fullStr Orphelia: predicting genes in metagenomic sequencing reads
title_full_unstemmed Orphelia: predicting genes in metagenomic sequencing reads
title_short Orphelia: predicting genes in metagenomic sequencing reads
title_sort orphelia: predicting genes in metagenomic sequencing reads
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2703946/
https://www.ncbi.nlm.nih.gov/pubmed/19429689
http://dx.doi.org/10.1093/nar/gkp327
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