Index-based approach to similarity search in protein and nucleotide databases

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F07%3A00206200" target="_blank" >RIV/00216208:11320/07:00206200 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Index-based approach to similarity search in protein and nucleotide databases
Original language 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. Thesequence 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 anapproach 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.
Czech name
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Czech description
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Project
<a href="/en/project/GP201%2F05%2FP036" target="_blank" >GP201/05/P036: Efficient metric search in large multimedia databases</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>Z - Vyzkumny zamer (s odkazem do CEZ)

Publication year
2007
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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