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UProC: tools for ultra-fast protein domain classification

Motivation: With rapidly increasing volumes of biological sequence data the functional analysis of new sequences in terms of similarities to known protein families challenges classical bioinformatics. Results: The ultrafast protein classification (UProC) toolbox implements a novel algorithm (‘Mosaic...

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Detalles Bibliográficos
Autor principal: Meinicke, Peter
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4410661/
https://www.ncbi.nlm.nih.gov/pubmed/25540185
http://dx.doi.org/10.1093/bioinformatics/btu843
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author Meinicke, Peter
author_facet Meinicke, Peter
author_sort Meinicke, Peter
collection PubMed
description Motivation: With rapidly increasing volumes of biological sequence data the functional analysis of new sequences in terms of similarities to known protein families challenges classical bioinformatics. Results: The ultrafast protein classification (UProC) toolbox implements a novel algorithm (‘Mosaic Matching’) for large-scale sequence analysis. UProC is by three orders of magnitude faster than profile-based methods and in a metagenome simulation study achieved up to 80% higher sensitivity on unassembled 100 bp reads. Availability and implementation: UProC is available as an open-source software at https://github.com/gobics/uproc. Precompiled databases (Pfam) are linked on the UProC homepage: http://uproc.gobics.de/. Contact: peter@gobics.de. Supplementary information: Supplementary data are available at Bioinformatics online.
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spelling pubmed-44106612015-04-30 UProC: tools for ultra-fast protein domain classification Meinicke, Peter Bioinformatics Original Papers Motivation: With rapidly increasing volumes of biological sequence data the functional analysis of new sequences in terms of similarities to known protein families challenges classical bioinformatics. Results: The ultrafast protein classification (UProC) toolbox implements a novel algorithm (‘Mosaic Matching’) for large-scale sequence analysis. UProC is by three orders of magnitude faster than profile-based methods and in a metagenome simulation study achieved up to 80% higher sensitivity on unassembled 100 bp reads. Availability and implementation: UProC is available as an open-source software at https://github.com/gobics/uproc. Precompiled databases (Pfam) are linked on the UProC homepage: http://uproc.gobics.de/. Contact: peter@gobics.de. Supplementary information: Supplementary data are available at Bioinformatics online. Oxford University Press 2015-05-01 2014-12-23 /pmc/articles/PMC4410661/ /pubmed/25540185 http://dx.doi.org/10.1093/bioinformatics/btu843 Text en © The Author 2014. Published by Oxford University Press. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Papers
Meinicke, Peter
UProC: tools for ultra-fast protein domain classification
title UProC: tools for ultra-fast protein domain classification
title_full UProC: tools for ultra-fast protein domain classification
title_fullStr UProC: tools for ultra-fast protein domain classification
title_full_unstemmed UProC: tools for ultra-fast protein domain classification
title_short UProC: tools for ultra-fast protein domain classification
title_sort uproc: tools for ultra-fast protein domain classification
topic Original Papers
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4410661/
https://www.ncbi.nlm.nih.gov/pubmed/25540185
http://dx.doi.org/10.1093/bioinformatics/btu843
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