Design and implementation of a database filter for BLAST acceleration

Afratis,; Galanakis,; Sotiriades,; Mplemenos,; Chrysos,; Papaefstathiou, Ioannis; Pnevmatikatos,

doi:10.1109/date.2009.5090652

Cited by 3 publications

(2 citation statements)

References 7 publications

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“…Over the years several modifications to the fundamental algorithms and new heuristics in BLAST were proposed to improve speed and minimize runtime space [3][4][5][6][7], [10][11][12][13][14][15][16]. Manuscript This paper proposes modified data structure that reduces the runtime space during the hit detection stage of the FSA protein BLAST algorithm.…”

Section: Introductionmentioning

confidence: 99%

Improved Hit Detection Algorithm for FSA Protein BLAST

Anuradha¹,

Nelson²,

Reddy³

2012

IJBBB

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Abstract-Basic Local Alignment Search Tool (BLAST) is one of the most widely used bioinformatics tools to determine similarities between genomic sequences. Ever since its inception several algorithmic improvements have been made to improve speed and runtime memory requirements without affecting the sensitivity and selectivity of the tool. Fast search algorithm (FSA) BLAST has been the most successful among such improvements with 20-30% faster processing rate. In this work a modified data structure is used for the hit detection process. Codes have been developed separately for use of existing and modified data structures and tested on sample database. It has been found that the use of new data structure results in up to 81% reduction in run time memory requirement and about 20% reduction in hit detection time without affecting sensitivity and selectivity of the algorithm.

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Section: Introductionmentioning

confidence: 99%

Improved Hit Detection Algorithm for FSA Protein BLAST

Anuradha¹,

Nelson²,

Reddy³

2012

IJBBB

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“…Over the years several modifications to the fundamental algorithms and new heuristics in BLAST were proposed to improve speed and minimize runtime space [3][4][5][6][7], [11][12][13][14][15][16][17][18]. Basically, BLAST program was designed to analyze both protein and DNA sequences.…”

Section: Introductionmentioning

confidence: 99%

BLOSUM Trie for Faster Hit Detection in FSA Protein BLAST

Anuradha¹,

Nelson²,

Reddy³

2013

IJCA

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Basic Local Alignment Search Tool (BLAST) is one of the most widely used bioinformatics tools to determine similarities between genomic sequences. Ever since its inception several algorithmic improvements have been made to improve speed and runtime memory requirements without affecting the sensitivity and selectivity of the tool. Fast search algorithm (FSA) BLAST has been the most successful among such improvements with 20-30% faster processing rate. A DFA with hashed prefix word structures for the hit detection process in FSA BLAST has been proposed in the earlier work. Coding of the algorithms and testing on protein samples showed that the use of the new structure resulted in significant reduction in run time space but not the hit detection time. This paper proposes the use of a BLOSUM trie structure which eliminates the process of computing neighborhood words, resulted in a reduction of up to 75% in hit detection time. Tests were conducted with different BLOSUM matrices and threshold values and the proposed algorithm was found to be beneficial in terms of space, time complexity and accuracy without compromising on sensitivity and selectivity of the currently being used algorithm.

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Reconfigurable Architectures for Bioinformatics Applications

Dollas

2010

2010 IEEE Computer Society Annual Symposium on VLSI

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Design and implementation of a database filter for BLAST acceleration

Cited by 3 publications

References 7 publications

Improved Hit Detection Algorithm for FSA Protein BLAST

Improved Hit Detection Algorithm for FSA Protein BLAST

BLOSUM Trie for Faster Hit Detection in FSA Protein BLAST

Reconfigurable Architectures for Bioinformatics Applications

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