The R*-tree: an efficient and robust access method for points and rectangles
SIGMOD '90 Proceedings of the 1990 ACM SIGMOD international conference on Management of data
String searching algorithms
Tries for Approximate String Matching
IEEE Transactions on Knowledge and Data Engineering
Indexing and Retrieval for Genomic Databases
IEEE Transactions on Knowledge and Data Engineering
Database indexing for large DNA and protein sequence collections
The VLDB Journal — The International Journal on Very Large Data Bases
Approximate String-Matching over Suffix Trees
CPM '93 Proceedings of the 4th Annual Symposium on Combinatorial Pattern Matching
BLAST++: a tool for BLASTing queries in batches
APBC '03 Proceedings of the First Asia-Pacific bioinformatics conference on Bioinformatics 2003 - Volume 19
OASIS: an online and accurate technique for local-alignment searches on biological sequences
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
A practical method for approximate subsequence search in DNA databases
PAKDD'07 Proceedings of the 11th Pacific-Asia conference on Advances in knowledge discovery and data mining
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In molecular biology, DNA sequence matching is one of the most crucial operations. Since DNA databases contain a huge volume of sequences, fast indexes are essential for efficient processing of DNA sequence matching. In this paper, we first point out the problems of the suffix tree, an index structure widely-used for DNA sequence matching, in the respects of the storage overhead, search performance, and difficulty in seamless integration with DBMS. Then, we propose a new index structure that resolves such problems. The proposed index structure consists of the two parts: the primary part realizes the trie as binary bit-string representation without any pointers, and the secondary part helps fast accesses of leaf nodes of the trie that need to be accessed for post-processing. We also suggest efficient algorithms based on that index for DNA sequence matching. To verify the superiority of the proposed approach, we conduct performance evaluation via a series of experiments. The results reveal that the proposed approach, which requires smaller storage space, can be a few orders of magnitude faster than the suffix tree.