2000
DOI: 10.1089/10665270050081478
|View full text |Cite
|
Sign up to set email alerts
|

A Greedy Algorithm for Aligning DNA Sequences

Abstract: For aligning DNA sequences that differ only by sequencing errors, or by equivalent errors from other sources, a greedy algorithm can be much faster than traditional dynamic programming approaches and yet produce an alignment that is guaranteed to be theoretically optimal. We introduce a new greedy alignment algorithm with particularly good performance and show that it computes the same alignment as does a certain dynamic programming algorithm, while executing over 10 times faster on appropriate data. An implem… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
3
1
1

Citation Types

7
3,157
0
38

Year Published

2001
2001
2017
2017

Publication Types

Select...
7
2

Relationship

0
9

Authors

Journals

citations
Cited by 4,576 publications
(3,318 citation statements)
references
References 21 publications
7
3,157
0
38
Order By: Relevance
“…The complete sequences of all segments of each isolate were compared using the Basic Local Alignment Search Tool (BLAST) to identify the most closely related sequences available in public databases 35. The nucleotide sequences of each gene segment were aligned using clc genomics workbench version 7.6 (Qiagen, Aarhus, Denmark), and the percentage nucleotide similarity was calculated using the MegAlign program of the dnastar package (DNASTAR, Inc., Madison, WI, USA).…”
Section: Methodsmentioning
confidence: 99%
“…The complete sequences of all segments of each isolate were compared using the Basic Local Alignment Search Tool (BLAST) to identify the most closely related sequences available in public databases 35. The nucleotide sequences of each gene segment were aligned using clc genomics workbench version 7.6 (Qiagen, Aarhus, Denmark), and the percentage nucleotide similarity was calculated using the MegAlign program of the dnastar package (DNASTAR, Inc., Madison, WI, USA).…”
Section: Methodsmentioning
confidence: 99%
“…The 33‐ to 64‐bp nucleotide sequences (hereafter “tags”) flanking sequenced ApeKI restriction sites associated with these SNPs were used in a BLASTALL v2.2.26 (Zhang et al. 2000) blastn search against an un‐annotated, normalized, 33.2‐Mbp expressed sequence tag (EST) library assembly derived from a single North American A. artemisiifolia individual collected in Minnesota (Lai et al. 2012), using an E‐value threshold of 10 −10 and reporting at most five best hits.…”
Section: Methodsmentioning
confidence: 99%
“…Both observations are attributable to the alignment algorithm used. First, the shorter local alignments are caused by the extension algorithm of the local alignment program, which extends the alignment only as long as the score does not drop by a certain value below the previous maximal score by aligning further bases [22,24]. The extension of the alignment will therefore stop earlier if the target genome is more distantly related, thus leading to shorter local alignments.…”
Section: Resultsmentioning
confidence: 99%
“…While necessity has required the use of fast local alignment programs such as BLAST [23], Mega BLAST [24] or BLASTZ [25] when handling such large datasets, the exact classification and filtering regimes have not been standardized or even comprehensively examined. In the most straight-forward classification scheme, reads that match a specific target genome with sufficient similarity are classified as endogenous (that is, from the target species) [11,13].…”
Section: Introductionmentioning
confidence: 99%