Index-Based Approach to Similarity Search in Protein and Nucleotide Databases
David Hoksza, Tomáš Skopal · 2007
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 eciency of retrieval methods becomes the critical issue. The sequence retrieval re- lies 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 approxima- tion 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 exper- imental results have shown that a straightforward adoption of MAMs to sequence retrieval cannot outperform the specialized heuristic algo- rithms (at least at the moment). On the other side, the results show MAMs could provide a basis for specialized access methods capable of precision/ecienc y trade-o control.