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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...
Autores principales: | , , , |
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Formato: | Texto |
Lenguaje: | English |
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BioMed Central
2008
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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. |
format | Text |
id | pubmed-2246154 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2008 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
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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