Lossless filter for multiple repeats with bounded edit distance

Background Identifying local similarity between two or more sequences, or identifying repeats occurring at least twice in a sequence, is an essential part in the analysis of biological sequences and of their phylogenetic relationship. Finding such fragments while allowing for a certain number of ins...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Peterlongo, Pierre [verfasserIn] Sacomoto, Gustavo Akio Tominaga do Lago, Alair Pereira Pisanti, Nadia Sagot, Marie-France

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2009

Schlagwörter:	Transposable Element Cystic Fibrosis Transmembrane Conductance Regulator Edit Distance Edit Operation Multiple Repeat

Anmerkung:	© Peterlongo et al; licensee BioMed Central Ltd. 2009

Übergeordnetes Werk:	Enthalten in: Algorithms for molecular biology - London : BioMed Central, 2006, 4(2009), 1 vom: 30. Jan.
Übergeordnetes Werk:	volume:4 ; year:2009 ; number:1 ; day:30 ; month:01

Links:	Volltext

DOI / URN:	10.1186/1748-7188-4-3

Katalog-ID:	SPR029837944

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245	1	0	\|a Lossless filter for multiple repeats with bounded edit distance
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500			\|a © Peterlongo et al; licensee BioMed Central Ltd. 2009
520			\|a Background Identifying local similarity between two or more sequences, or identifying repeats occurring at least twice in a sequence, is an essential part in the analysis of biological sequences and of their phylogenetic relationship. Finding such fragments while allowing for a certain number of insertions, deletions, and substitutions, is however known to be a computationally expensive task, and consequently exact methods can usually not be applied in practice. Results The filter TUIUIU that we introduce in this paper provides a possible solution to this problem. It can be used as a preprocessing step to any multiple alignment or repeats inference method, eliminating a possibly large fraction of the input that is guaranteed not to contain any approximate repeat. It consists in the verification of several strong necessary conditions that can be checked in a fast way. We implemented three versions of the filter. The first is simply a straightforward extension to the case of multiple sequences of an application of conditions already existing in the literature. The second uses a stronger condition which, as our results show, enable to filter sensibly more with negligible (if any) additional time. The third version uses an additional condition and pushes the sensibility of the filter even further with a non negligible additional time in many circumstances; our experiments show that it is particularly useful with large error rates. The latter version was applied as a preprocessing of a multiple alignment tool, obtaining an overall time (filter plus alignment) on average 63 and at best 530 times smaller than before (direct alignment), with in most cases a better quality alignment. Conclusion To the best of our knowledge, TUIUIU is the first filter designed for multiple repeats and for dealing with error rates greater than 10% of the repeats length.
650		4	\|a Transposable Element \|7 (dpeaa)DE-He213
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650		4	\|a Edit Distance \|7 (dpeaa)DE-He213
650		4	\|a Edit Operation \|7 (dpeaa)DE-He213
650		4	\|a Multiple Repeat \|7 (dpeaa)DE-He213
700	1		\|a Sacomoto, Gustavo Akio Tominaga \|4 aut
700	1		\|a do Lago, Alair Pereira \|4 aut
700	1		\|a Pisanti, Nadia \|4 aut
700	1		\|a Sagot, Marie-France \|4 aut
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912			\|a GBV_USEFLAG_A
912			\|a SYSFLAG_A
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912			\|a GBV_ILN_20
912			\|a GBV_ILN_22
912			\|a GBV_ILN_23
912			\|a GBV_ILN_24
912			\|a GBV_ILN_39
912			\|a GBV_ILN_40
912			\|a GBV_ILN_62
912			\|a GBV_ILN_63
912			\|a GBV_ILN_65
912			\|a GBV_ILN_69
912			\|a GBV_ILN_70
912			\|a GBV_ILN_73
912			\|a GBV_ILN_74
912			\|a GBV_ILN_95
912			\|a GBV_ILN_105
912			\|a GBV_ILN_110
912			\|a GBV_ILN_151
912			\|a GBV_ILN_161
912			\|a GBV_ILN_170
912			\|a GBV_ILN_206
912			\|a GBV_ILN_213
912			\|a GBV_ILN_230
912			\|a GBV_ILN_285
912			\|a GBV_ILN_293
912			\|a GBV_ILN_602
912			\|a GBV_ILN_2003
912			\|a GBV_ILN_2005
912			\|a GBV_ILN_2009
912			\|a GBV_ILN_2011
912			\|a GBV_ILN_2014
912			\|a GBV_ILN_2027
912			\|a GBV_ILN_2055
912			\|a GBV_ILN_2111
912			\|a GBV_ILN_4012
912			\|a GBV_ILN_4037
912			\|a GBV_ILN_4112
912			\|a GBV_ILN_4125
912			\|a GBV_ILN_4126
912			\|a GBV_ILN_4249
912			\|a GBV_ILN_4305
912			\|a GBV_ILN_4306
912			\|a GBV_ILN_4307
912			\|a GBV_ILN_4313
912			\|a GBV_ILN_4322
912			\|a GBV_ILN_4323
912			\|a GBV_ILN_4324
912			\|a GBV_ILN_4325
912			\|a GBV_ILN_4338
912			\|a GBV_ILN_4367
912			\|a GBV_ILN_4700
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allfields	10.1186/1748-7188-4-3 doi (DE-627)SPR029837944 (SPR)1748-7188-4-3-e DE-627 ger DE-627 rakwb eng Peterlongo, Pierre verfasserin aut Lossless filter for multiple repeats with bounded edit distance 2009 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Peterlongo et al; licensee BioMed Central Ltd. 2009 Background Identifying local similarity between two or more sequences, or identifying repeats occurring at least twice in a sequence, is an essential part in the analysis of biological sequences and of their phylogenetic relationship. Finding such fragments while allowing for a certain number of insertions, deletions, and substitutions, is however known to be a computationally expensive task, and consequently exact methods can usually not be applied in practice. Results The filter TUIUIU that we introduce in this paper provides a possible solution to this problem. It can be used as a preprocessing step to any multiple alignment or repeats inference method, eliminating a possibly large fraction of the input that is guaranteed not to contain any approximate repeat. It consists in the verification of several strong necessary conditions that can be checked in a fast way. We implemented three versions of the filter. The first is simply a straightforward extension to the case of multiple sequences of an application of conditions already existing in the literature. The second uses a stronger condition which, as our results show, enable to filter sensibly more with negligible (if any) additional time. The third version uses an additional condition and pushes the sensibility of the filter even further with a non negligible additional time in many circumstances; our experiments show that it is particularly useful with large error rates. The latter version was applied as a preprocessing of a multiple alignment tool, obtaining an overall time (filter plus alignment) on average 63 and at best 530 times smaller than before (direct alignment), with in most cases a better quality alignment. Conclusion To the best of our knowledge, TUIUIU is the first filter designed for multiple repeats and for dealing with error rates greater than 10% of the repeats length. Transposable Element (dpeaa)DE-He213 Cystic Fibrosis Transmembrane Conductance Regulator (dpeaa)DE-He213 Edit Distance (dpeaa)DE-He213 Edit Operation (dpeaa)DE-He213 Multiple Repeat (dpeaa)DE-He213 Sacomoto, Gustavo Akio Tominaga aut do Lago, Alair Pereira aut Pisanti, Nadia aut Sagot, Marie-France aut Enthalten in Algorithms for molecular biology London : BioMed Central, 2006 4(2009), 1 vom: 30. Jan. (DE-627)508725755 (DE-600)2224970-9 1748-7188 nnns volume:4 year:2009 number:1 day:30 month:01 https://dx.doi.org/10.1186/1748-7188-4-3 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2027 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 4 2009 1 30 01
spelling	10.1186/1748-7188-4-3 doi (DE-627)SPR029837944 (SPR)1748-7188-4-3-e DE-627 ger DE-627 rakwb eng Peterlongo, Pierre verfasserin aut Lossless filter for multiple repeats with bounded edit distance 2009 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Peterlongo et al; licensee BioMed Central Ltd. 2009 Background Identifying local similarity between two or more sequences, or identifying repeats occurring at least twice in a sequence, is an essential part in the analysis of biological sequences and of their phylogenetic relationship. Finding such fragments while allowing for a certain number of insertions, deletions, and substitutions, is however known to be a computationally expensive task, and consequently exact methods can usually not be applied in practice. Results The filter TUIUIU that we introduce in this paper provides a possible solution to this problem. It can be used as a preprocessing step to any multiple alignment or repeats inference method, eliminating a possibly large fraction of the input that is guaranteed not to contain any approximate repeat. It consists in the verification of several strong necessary conditions that can be checked in a fast way. We implemented three versions of the filter. The first is simply a straightforward extension to the case of multiple sequences of an application of conditions already existing in the literature. The second uses a stronger condition which, as our results show, enable to filter sensibly more with negligible (if any) additional time. The third version uses an additional condition and pushes the sensibility of the filter even further with a non negligible additional time in many circumstances; our experiments show that it is particularly useful with large error rates. The latter version was applied as a preprocessing of a multiple alignment tool, obtaining an overall time (filter plus alignment) on average 63 and at best 530 times smaller than before (direct alignment), with in most cases a better quality alignment. Conclusion To the best of our knowledge, TUIUIU is the first filter designed for multiple repeats and for dealing with error rates greater than 10% of the repeats length. Transposable Element (dpeaa)DE-He213 Cystic Fibrosis Transmembrane Conductance Regulator (dpeaa)DE-He213 Edit Distance (dpeaa)DE-He213 Edit Operation (dpeaa)DE-He213 Multiple Repeat (dpeaa)DE-He213 Sacomoto, Gustavo Akio Tominaga aut do Lago, Alair Pereira aut Pisanti, Nadia aut Sagot, Marie-France aut Enthalten in Algorithms for molecular biology London : BioMed Central, 2006 4(2009), 1 vom: 30. Jan. (DE-627)508725755 (DE-600)2224970-9 1748-7188 nnns volume:4 year:2009 number:1 day:30 month:01 https://dx.doi.org/10.1186/1748-7188-4-3 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2027 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 4 2009 1 30 01
allfields_unstemmed	10.1186/1748-7188-4-3 doi (DE-627)SPR029837944 (SPR)1748-7188-4-3-e DE-627 ger DE-627 rakwb eng Peterlongo, Pierre verfasserin aut Lossless filter for multiple repeats with bounded edit distance 2009 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Peterlongo et al; licensee BioMed Central Ltd. 2009 Background Identifying local similarity between two or more sequences, or identifying repeats occurring at least twice in a sequence, is an essential part in the analysis of biological sequences and of their phylogenetic relationship. Finding such fragments while allowing for a certain number of insertions, deletions, and substitutions, is however known to be a computationally expensive task, and consequently exact methods can usually not be applied in practice. Results The filter TUIUIU that we introduce in this paper provides a possible solution to this problem. It can be used as a preprocessing step to any multiple alignment or repeats inference method, eliminating a possibly large fraction of the input that is guaranteed not to contain any approximate repeat. It consists in the verification of several strong necessary conditions that can be checked in a fast way. We implemented three versions of the filter. The first is simply a straightforward extension to the case of multiple sequences of an application of conditions already existing in the literature. The second uses a stronger condition which, as our results show, enable to filter sensibly more with negligible (if any) additional time. The third version uses an additional condition and pushes the sensibility of the filter even further with a non negligible additional time in many circumstances; our experiments show that it is particularly useful with large error rates. The latter version was applied as a preprocessing of a multiple alignment tool, obtaining an overall time (filter plus alignment) on average 63 and at best 530 times smaller than before (direct alignment), with in most cases a better quality alignment. Conclusion To the best of our knowledge, TUIUIU is the first filter designed for multiple repeats and for dealing with error rates greater than 10% of the repeats length. Transposable Element (dpeaa)DE-He213 Cystic Fibrosis Transmembrane Conductance Regulator (dpeaa)DE-He213 Edit Distance (dpeaa)DE-He213 Edit Operation (dpeaa)DE-He213 Multiple Repeat (dpeaa)DE-He213 Sacomoto, Gustavo Akio Tominaga aut do Lago, Alair Pereira aut Pisanti, Nadia aut Sagot, Marie-France aut Enthalten in Algorithms for molecular biology London : BioMed Central, 2006 4(2009), 1 vom: 30. Jan. (DE-627)508725755 (DE-600)2224970-9 1748-7188 nnns volume:4 year:2009 number:1 day:30 month:01 https://dx.doi.org/10.1186/1748-7188-4-3 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2027 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 4 2009 1 30 01
allfieldsGer	10.1186/1748-7188-4-3 doi (DE-627)SPR029837944 (SPR)1748-7188-4-3-e DE-627 ger DE-627 rakwb eng Peterlongo, Pierre verfasserin aut Lossless filter for multiple repeats with bounded edit distance 2009 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Peterlongo et al; licensee BioMed Central Ltd. 2009 Background Identifying local similarity between two or more sequences, or identifying repeats occurring at least twice in a sequence, is an essential part in the analysis of biological sequences and of their phylogenetic relationship. Finding such fragments while allowing for a certain number of insertions, deletions, and substitutions, is however known to be a computationally expensive task, and consequently exact methods can usually not be applied in practice. Results The filter TUIUIU that we introduce in this paper provides a possible solution to this problem. It can be used as a preprocessing step to any multiple alignment or repeats inference method, eliminating a possibly large fraction of the input that is guaranteed not to contain any approximate repeat. It consists in the verification of several strong necessary conditions that can be checked in a fast way. We implemented three versions of the filter. The first is simply a straightforward extension to the case of multiple sequences of an application of conditions already existing in the literature. The second uses a stronger condition which, as our results show, enable to filter sensibly more with negligible (if any) additional time. The third version uses an additional condition and pushes the sensibility of the filter even further with a non negligible additional time in many circumstances; our experiments show that it is particularly useful with large error rates. The latter version was applied as a preprocessing of a multiple alignment tool, obtaining an overall time (filter plus alignment) on average 63 and at best 530 times smaller than before (direct alignment), with in most cases a better quality alignment. Conclusion To the best of our knowledge, TUIUIU is the first filter designed for multiple repeats and for dealing with error rates greater than 10% of the repeats length. Transposable Element (dpeaa)DE-He213 Cystic Fibrosis Transmembrane Conductance Regulator (dpeaa)DE-He213 Edit Distance (dpeaa)DE-He213 Edit Operation (dpeaa)DE-He213 Multiple Repeat (dpeaa)DE-He213 Sacomoto, Gustavo Akio Tominaga aut do Lago, Alair Pereira aut Pisanti, Nadia aut Sagot, Marie-France aut Enthalten in Algorithms for molecular biology London : BioMed Central, 2006 4(2009), 1 vom: 30. Jan. (DE-627)508725755 (DE-600)2224970-9 1748-7188 nnns volume:4 year:2009 number:1 day:30 month:01 https://dx.doi.org/10.1186/1748-7188-4-3 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2027 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 4 2009 1 30 01
allfieldsSound	10.1186/1748-7188-4-3 doi (DE-627)SPR029837944 (SPR)1748-7188-4-3-e DE-627 ger DE-627 rakwb eng Peterlongo, Pierre verfasserin aut Lossless filter for multiple repeats with bounded edit distance 2009 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Peterlongo et al; licensee BioMed Central Ltd. 2009 Background Identifying local similarity between two or more sequences, or identifying repeats occurring at least twice in a sequence, is an essential part in the analysis of biological sequences and of their phylogenetic relationship. Finding such fragments while allowing for a certain number of insertions, deletions, and substitutions, is however known to be a computationally expensive task, and consequently exact methods can usually not be applied in practice. Results The filter TUIUIU that we introduce in this paper provides a possible solution to this problem. It can be used as a preprocessing step to any multiple alignment or repeats inference method, eliminating a possibly large fraction of the input that is guaranteed not to contain any approximate repeat. It consists in the verification of several strong necessary conditions that can be checked in a fast way. We implemented three versions of the filter. The first is simply a straightforward extension to the case of multiple sequences of an application of conditions already existing in the literature. The second uses a stronger condition which, as our results show, enable to filter sensibly more with negligible (if any) additional time. The third version uses an additional condition and pushes the sensibility of the filter even further with a non negligible additional time in many circumstances; our experiments show that it is particularly useful with large error rates. The latter version was applied as a preprocessing of a multiple alignment tool, obtaining an overall time (filter plus alignment) on average 63 and at best 530 times smaller than before (direct alignment), with in most cases a better quality alignment. Conclusion To the best of our knowledge, TUIUIU is the first filter designed for multiple repeats and for dealing with error rates greater than 10% of the repeats length. Transposable Element (dpeaa)DE-He213 Cystic Fibrosis Transmembrane Conductance Regulator (dpeaa)DE-He213 Edit Distance (dpeaa)DE-He213 Edit Operation (dpeaa)DE-He213 Multiple Repeat (dpeaa)DE-He213 Sacomoto, Gustavo Akio Tominaga aut do Lago, Alair Pereira aut Pisanti, Nadia aut Sagot, Marie-France aut Enthalten in Algorithms for molecular biology London : BioMed Central, 2006 4(2009), 1 vom: 30. Jan. (DE-627)508725755 (DE-600)2224970-9 1748-7188 nnns volume:4 year:2009 number:1 day:30 month:01 https://dx.doi.org/10.1186/1748-7188-4-3 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2027 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 4 2009 1 30 01
language	English
source	Enthalten in Algorithms for molecular biology 4(2009), 1 vom: 30. Jan. volume:4 year:2009 number:1 day:30 month:01
sourceStr	Enthalten in Algorithms for molecular biology 4(2009), 1 vom: 30. Jan. volume:4 year:2009 number:1 day:30 month:01
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Transposable Element Cystic Fibrosis Transmembrane Conductance Regulator Edit Distance Edit Operation Multiple Repeat
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container_title	Algorithms for molecular biology
authorswithroles_txt_mv	Peterlongo, Pierre @@aut@@ Sacomoto, Gustavo Akio Tominaga @@aut@@ do Lago, Alair Pereira @@aut@@ Pisanti, Nadia @@aut@@ Sagot, Marie-France @@aut@@
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author	Peterlongo, Pierre
spellingShingle	Peterlongo, Pierre misc Transposable Element misc Cystic Fibrosis Transmembrane Conductance Regulator misc Edit Distance misc Edit Operation misc Multiple Repeat Lossless filter for multiple repeats with bounded edit distance
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topic_title	Lossless filter for multiple repeats with bounded edit distance Transposable Element (dpeaa)DE-He213 Cystic Fibrosis Transmembrane Conductance Regulator (dpeaa)DE-He213 Edit Distance (dpeaa)DE-He213 Edit Operation (dpeaa)DE-He213 Multiple Repeat (dpeaa)DE-He213
topic	misc Transposable Element misc Cystic Fibrosis Transmembrane Conductance Regulator misc Edit Distance misc Edit Operation misc Multiple Repeat
topic_unstemmed	misc Transposable Element misc Cystic Fibrosis Transmembrane Conductance Regulator misc Edit Distance misc Edit Operation misc Multiple Repeat
topic_browse	misc Transposable Element misc Cystic Fibrosis Transmembrane Conductance Regulator misc Edit Distance misc Edit Operation misc Multiple Repeat
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title	Lossless filter for multiple repeats with bounded edit distance
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title_full	Lossless filter for multiple repeats with bounded edit distance
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title_sort	lossless filter for multiple repeats with bounded edit distance
title_auth	Lossless filter for multiple repeats with bounded edit distance
abstract	Background Identifying local similarity between two or more sequences, or identifying repeats occurring at least twice in a sequence, is an essential part in the analysis of biological sequences and of their phylogenetic relationship. Finding such fragments while allowing for a certain number of insertions, deletions, and substitutions, is however known to be a computationally expensive task, and consequently exact methods can usually not be applied in practice. Results The filter TUIUIU that we introduce in this paper provides a possible solution to this problem. It can be used as a preprocessing step to any multiple alignment or repeats inference method, eliminating a possibly large fraction of the input that is guaranteed not to contain any approximate repeat. It consists in the verification of several strong necessary conditions that can be checked in a fast way. We implemented three versions of the filter. The first is simply a straightforward extension to the case of multiple sequences of an application of conditions already existing in the literature. The second uses a stronger condition which, as our results show, enable to filter sensibly more with negligible (if any) additional time. The third version uses an additional condition and pushes the sensibility of the filter even further with a non negligible additional time in many circumstances; our experiments show that it is particularly useful with large error rates. The latter version was applied as a preprocessing of a multiple alignment tool, obtaining an overall time (filter plus alignment) on average 63 and at best 530 times smaller than before (direct alignment), with in most cases a better quality alignment. Conclusion To the best of our knowledge, TUIUIU is the first filter designed for multiple repeats and for dealing with error rates greater than 10% of the repeats length. © Peterlongo et al; licensee BioMed Central Ltd. 2009
abstractGer	Background Identifying local similarity between two or more sequences, or identifying repeats occurring at least twice in a sequence, is an essential part in the analysis of biological sequences and of their phylogenetic relationship. Finding such fragments while allowing for a certain number of insertions, deletions, and substitutions, is however known to be a computationally expensive task, and consequently exact methods can usually not be applied in practice. Results The filter TUIUIU that we introduce in this paper provides a possible solution to this problem. It can be used as a preprocessing step to any multiple alignment or repeats inference method, eliminating a possibly large fraction of the input that is guaranteed not to contain any approximate repeat. It consists in the verification of several strong necessary conditions that can be checked in a fast way. We implemented three versions of the filter. The first is simply a straightforward extension to the case of multiple sequences of an application of conditions already existing in the literature. The second uses a stronger condition which, as our results show, enable to filter sensibly more with negligible (if any) additional time. The third version uses an additional condition and pushes the sensibility of the filter even further with a non negligible additional time in many circumstances; our experiments show that it is particularly useful with large error rates. The latter version was applied as a preprocessing of a multiple alignment tool, obtaining an overall time (filter plus alignment) on average 63 and at best 530 times smaller than before (direct alignment), with in most cases a better quality alignment. Conclusion To the best of our knowledge, TUIUIU is the first filter designed for multiple repeats and for dealing with error rates greater than 10% of the repeats length. © Peterlongo et al; licensee BioMed Central Ltd. 2009
abstract_unstemmed	Background Identifying local similarity between two or more sequences, or identifying repeats occurring at least twice in a sequence, is an essential part in the analysis of biological sequences and of their phylogenetic relationship. Finding such fragments while allowing for a certain number of insertions, deletions, and substitutions, is however known to be a computationally expensive task, and consequently exact methods can usually not be applied in practice. Results The filter TUIUIU that we introduce in this paper provides a possible solution to this problem. It can be used as a preprocessing step to any multiple alignment or repeats inference method, eliminating a possibly large fraction of the input that is guaranteed not to contain any approximate repeat. It consists in the verification of several strong necessary conditions that can be checked in a fast way. We implemented three versions of the filter. The first is simply a straightforward extension to the case of multiple sequences of an application of conditions already existing in the literature. The second uses a stronger condition which, as our results show, enable to filter sensibly more with negligible (if any) additional time. The third version uses an additional condition and pushes the sensibility of the filter even further with a non negligible additional time in many circumstances; our experiments show that it is particularly useful with large error rates. The latter version was applied as a preprocessing of a multiple alignment tool, obtaining an overall time (filter plus alignment) on average 63 and at best 530 times smaller than before (direct alignment), with in most cases a better quality alignment. Conclusion To the best of our knowledge, TUIUIU is the first filter designed for multiple repeats and for dealing with error rates greater than 10% of the repeats length. © Peterlongo et al; licensee BioMed Central Ltd. 2009
collection_details	GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2027 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700
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title_short	Lossless filter for multiple repeats with bounded edit distance
url	https://dx.doi.org/10.1186/1748-7188-4-3
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author2	Sacomoto, Gustavo Akio Tominaga do Lago, Alair Pereira Pisanti, Nadia Sagot, Marie-France
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up_date	2024-07-04T02:27:25.249Z
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Lossless filter for multiple repeats with bounded edit distance

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