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Statements

Subject Item
n2:RIV%2F00216208%3A11320%2F07%3A00005162%21RIV08-MSM-11320___
rdf:type
n11:Vysledek skos:Concept
dcterms:description
When searching databases of nucleotide or protein sequences, finding a local alignment of two sequences is one of the main tasks. Since the sizes of available databases grow constantly, the efficiency of retrieval methods becomes the critical issue. The sequence retrieval relies on finding sequences in the database which align best with the query sequence. However, an optimal alignment can be found in quadratic time (by use of dynamic programming) while this is infeasible when dealing with large databases. The existing solutions use fast heuristic methods (like BLAST, FASTA) which produce only an uncontrolled approximation of the best alignment and even do not provide any information about the alignment approximation error. In this paper we propose an approach of exact and approximate indexing using several metric access methods (MAMs) in combination with the TriGen algorithm, in order to reduce the number of alignments (distance computations) needed. The experimental results have shown that a straigh Indexový přístup k podobnostnímu vyhledávání v proteinových a nukleotidových databázích When searching databases of nucleotide or protein sequences, finding a local alignment of two sequences is one of the main tasks. Since the sizes of available databases grow constantly, the efficiency of retrieval methods becomes the critical issue. The sequence retrieval relies on finding sequences in the database which align best with the query sequence. However, an optimal alignment can be found in quadratic time (by use of dynamic programming) while this is infeasible when dealing with large databases. The existing solutions use fast heuristic methods (like BLAST, FASTA) which produce only an uncontrolled approximation of the best alignment and even do not provide any information about the alignment approximation error. In this paper we propose an approach of exact and approximate indexing using several metric access methods (MAMs) in combination with the TriGen algorithm, in order to reduce the number of alignments (distance computations) needed. The experimental results have shown that a straigh
dcterms:title
Index-based approach to similarity search in protein and nucleotide databases Index-based approach to similarity search in protein and nucleotide databases Indexový přístup k podobnostnímu vyhledávání v proteinových a nukleotidových databázích
skos:prefLabel
Index-based approach to similarity search in protein and nucleotide databases Indexový přístup k podobnostnímu vyhledávání v proteinových a nukleotidových databázích Index-based approach to similarity search in protein and nucleotide databases
skos:notation
RIV/00216208:11320/07:00005162!RIV08-MSM-11320___
n3:strany
67;80
n3:aktivita
n10:P n10:Z
n3:aktivity
P(GP201/05/P036), Z(MSM0021620838)
n3:cisloPeriodika
Neuveden
n3:dodaniDat
n16:2008
n3:domaciTvurceVysledku
n8:9268421 n8:5851726
n3:druhVysledku
n4:J
n3:duvernostUdaju
n18:S
n3:entitaPredkladatele
n17:predkladatel
n3:idSjednocenehoVysledku
425967
n3:idVysledku
RIV/00216208:11320/07:00005162
n3:jazykVysledku
n13:eng
n3:klicovaSlova
Index-based; approach; similarity; search; protein; nucleotide; databases
n3:klicoveSlovo
n5:Index-based n5:search n5:nucleotide n5:databases n5:approach n5:protein n5:similarity
n3:kodStatuVydavatele
GB - Spojené království Velké Británie a Severního Irska
n3:kontrolniKodProRIV
[FA90C13E1BC3]
n3:nazevZdroje
CEUR Workshop Proceedings
n3:obor
n15:JC
n3:pocetDomacichTvurcuVysledku
2
n3:pocetTvurcuVysledku
2
n3:projekt
n7:GP201%2F05%2FP036
n3:rokUplatneniVysledku
n16:2007
n3:svazekPeriodika
235
n3:tvurceVysledku
Skopal, Tomáš Hoksza, David
n3:zamer
n12:MSM0021620838
s:issn
1613-0073
s:numberOfPages
14
n19:organizacniJednotka
11320