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

<p>Abstract</p> <p>Background</p> <p>The use of novel algorithmic techniques is pivotal to many important problems in life science. For example the sequencing of the human genome <abbrgrp><abbr bid="B1">1</abbr></abbrgrp> would not have...

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Main Authors: Rausch Tobias, Weese David, Döring Andreas, Reinert Knut
Format: Article
Language:English
Published: BMC 2008-01-01
Series:BMC Bioinformatics
Online Access:http://www.biomedcentral.com/1471-2105/9/11
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spelling doaj-efa7f3a130a749e88e3580884d8dc7d02020-11-24T20:44:29ZengBMCBMC Bioinformatics1471-21052008-01-01911110.1186/1471-2105-9-11SeqAn An efficient, generic C++ library for sequence analysisRausch TobiasWeese DavidDöring AndreasReinert Knut<p>Abstract</p> <p>Background</p> <p>The use of novel algorithmic techniques is pivotal to many important problems in life science. For example the sequencing of the human genome <abbrgrp><abbr bid="B1">1</abbr></abbrgrp> 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.</p> <p>Results</p> <p>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.</p> <p>Conclusion</p> <p>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.</p> http://www.biomedcentral.com/1471-2105/9/11
collection DOAJ
language English
format Article
sources DOAJ
author Rausch Tobias
Weese David
Döring Andreas
Reinert Knut
spellingShingle Rausch Tobias
Weese David
Döring Andreas
Reinert Knut
SeqAn An efficient, generic C++ library for sequence analysis
BMC Bioinformatics
author_facet Rausch Tobias
Weese David
Döring Andreas
Reinert Knut
author_sort Rausch Tobias
title SeqAn An efficient, generic C++ library for sequence analysis
title_short 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_sort seqan an efficient, generic c++ library for sequence analysis
publisher BMC
series BMC Bioinformatics
issn 1471-2105
publishDate 2008-01-01
description <p>Abstract</p> <p>Background</p> <p>The use of novel algorithmic techniques is pivotal to many important problems in life science. For example the sequencing of the human genome <abbrgrp><abbr bid="B1">1</abbr></abbrgrp> 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.</p> <p>Results</p> <p>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.</p> <p>Conclusion</p> <p>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.</p>
url http://www.biomedcentral.com/1471-2105/9/11
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