Fundamentals of data structures in PASCAL
Fundamentals of data structures in PASCAL
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
Suffix arrays: a new method for on-line string searches
SIAM Journal on Computing
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
FLASH: A Fast Look-Up Algorithm for String Homology
Proceedings of the 1st International Conference on Intelligent Systems for Molecular Biology
Efficient Index Structures for String Databases
Proceedings of the 27th International Conference 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
Developing Bioinformatics Computer Skills
Developing Bioinformatics Computer Skills
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
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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 respect of 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 two parts: the primary part realizes the trie as binary bit-string representation without any pointers, and the secondary part helps fast access to the trie's leaf nodes 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.