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SeqAn An efficient, generic C++ library for sequence analysis

BACKGROUND: The use of novel algorithmic techniques is pivotal to many important problems in life science. For example the sequencing of the human genome [1] would not have been possible without advanced assembly algorithms. However, owing to the high speed of technological progress and the urgent n...

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Detalles Bibliográficos
Autores principales: Döring, Andreas, Weese, David, Rausch, Tobias, Reinert, Knut
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2008
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2246154/
https://www.ncbi.nlm.nih.gov/pubmed/18184432
http://dx.doi.org/10.1186/1471-2105-9-11
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author Döring, Andreas
Weese, David
Rausch, Tobias
Reinert, Knut
author_facet Döring, Andreas
Weese, David
Rausch, Tobias
Reinert, Knut
author_sort Döring, Andreas
collection PubMed
description BACKGROUND: The use of novel algorithmic techniques is pivotal to many important problems in life science. For example the sequencing of the human genome [1] would not have been possible without advanced assembly algorithms. However, owing to the high speed of technological progress and the urgent need for bioinformatics tools, there is a widening gap between state-of-the-art algorithmic techniques and the actual algorithmic components of tools that are in widespread use. RESULTS: To remedy this trend we propose the use of SeqAn, a library of efficient data types and algorithms for sequence analysis in computational biology. SeqAn comprises implementations of existing, practical state-of-the-art algorithmic components to provide a sound basis for algorithm testing and development. In this paper we describe the design and content of SeqAn and demonstrate its use by giving two examples. In the first example we show an application of SeqAn as an experimental platform by comparing different exact string matching algorithms. The second example is a simple version of the well-known MUMmer tool rewritten in SeqAn. Results indicate that our implementation is very efficient and versatile to use. CONCLUSION: We anticipate that SeqAn greatly simplifies the rapid development of new bioinformatics tools by providing a collection of readily usable, well-designed algorithmic components which are fundamental for the field of sequence analysis. This leverages not only the implementation of new algorithms, but also enables a sound analysis and comparison of existing algorithms.
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spelling pubmed-22461542008-02-19 SeqAn An efficient, generic C++ library for sequence analysis Döring, Andreas Weese, David Rausch, Tobias Reinert, Knut BMC Bioinformatics Software BACKGROUND: The use of novel algorithmic techniques is pivotal to many important problems in life science. For example the sequencing of the human genome [1] would not have been possible without advanced assembly algorithms. However, owing to the high speed of technological progress and the urgent need for bioinformatics tools, there is a widening gap between state-of-the-art algorithmic techniques and the actual algorithmic components of tools that are in widespread use. RESULTS: To remedy this trend we propose the use of SeqAn, a library of efficient data types and algorithms for sequence analysis in computational biology. SeqAn comprises implementations of existing, practical state-of-the-art algorithmic components to provide a sound basis for algorithm testing and development. In this paper we describe the design and content of SeqAn and demonstrate its use by giving two examples. In the first example we show an application of SeqAn as an experimental platform by comparing different exact string matching algorithms. The second example is a simple version of the well-known MUMmer tool rewritten in SeqAn. Results indicate that our implementation is very efficient and versatile to use. CONCLUSION: We anticipate that SeqAn greatly simplifies the rapid development of new bioinformatics tools by providing a collection of readily usable, well-designed algorithmic components which are fundamental for the field of sequence analysis. This leverages not only the implementation of new algorithms, but also enables a sound analysis and comparison of existing algorithms. BioMed Central 2008-01-09 /pmc/articles/PMC2246154/ /pubmed/18184432 http://dx.doi.org/10.1186/1471-2105-9-11 Text en Copyright © 2008 Döring et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Software
Döring, Andreas
Weese, David
Rausch, Tobias
Reinert, Knut
SeqAn An efficient, generic C++ library for sequence analysis
title SeqAn An efficient, generic C++ library for sequence analysis
title_full SeqAn An efficient, generic C++ library for sequence analysis
title_fullStr SeqAn An efficient, generic C++ library for sequence analysis
title_full_unstemmed SeqAn An efficient, generic C++ library for sequence analysis
title_short SeqAn An efficient, generic C++ library for sequence analysis
title_sort seqan an efficient, generic c++ library for sequence analysis
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2246154/
https://www.ncbi.nlm.nih.gov/pubmed/18184432
http://dx.doi.org/10.1186/1471-2105-9-11
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