Fast computation of neighbor seeds

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Fast computation of neighbor seeds

MOTIVATION Alignment of biological sequences is one of the most frequently performed computer tasks. The current state of the art involves the use of (multiple) spaced seeds for producing high quality alignments. A particular important class is that of neighbor seeds which combine high sensitivity with reduced space requirements. Current algorithms for computing good neighbor seeds are very slo...

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SpEED: fast computation of sensitive spaced seeds

SUMMARY Multiple spaced seeds represent the current state-of-the-art for similarity search in bioinformatics, with applications in various areas such as sequence alignment, read mapping, oligonucleotide design, etc. We present SpEED, a software program that computes highly sensitive multiple spaced seeds. SpEED can be several orders of magnitude faster and computes better seeds than the existin...

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Fast Computation of Good Multiple Spaced Seeds

Homology search finds similar segments between two biological sequences, such as DNA or protein sequences. A significant fraction of computing power in the world is dedicated to performing such tasks. The introduction of optimal spaced seeds by Ma et al. has increased both the sensitivity and the speed of homology search and it has been adopted by many alignment programs such as BLAST. With the...

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Efficient Seeds Computation Revisited

The notion of the cover is a generalization of a period of a string, and there are linear time algorithms for finding the shortest cover. The seed is a more complicated generalization of periodicity, it is a cover of a superstring of a given string, and the shortest seed problem is of much higher algorithmic difficulty. The problem is not well understood, no linear time algorithm is known. In t...

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Fast Neighbor Joining

Reconstructing the evolutionary history of a set of species is a fundamental problem in biology and methods for solving this problem are gaged based on two characteristics: accuracy and efficiency. Neighbor Joining (NJ) is a so-called distance-based method that, thanks to its good accuracy and speed, has been embraced by the phylogeny community. It takes the distances between n taxa and produce...

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ژورنال

عنوان ژورنال: Bioinformatics

سال: 2009

ISSN: 1367-4803,1460-2059

DOI: 10.1093/bioinformatics/btp054