Search-Optimized Suffix-Tree Storage for Biological Applications | Zendy

Srikanta Bedathur | Zendy; Jayant R. Haritsa | Zendy

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Search-Optimized Suffix-Tree Storage for Biological Applications

Author(s) -

Srikanta Bedathur,

Jayant R. Haritsa

Publication year - 2005

Publication title -

lecture notes in computer science

Language(s) - English

Resource type - Book series

SCImago Journal Rank - 0.249

H-Index - 400

eISSN - 1611-3349

pISSN - 0302-9743

ISBN - 3-540-30936-5

DOI - 10.1007/11602569_8

Subject(s) - suffix tree , generalized suffix tree , computer science , search engine indexing , suffix , compressed suffix array , set (abstract data type) , exploit , tree (set theory) , suffix array , sequence (biology) , trie , data structure , theoretical computer science , data mining , information retrieval , programming language , mathematics , mathematical analysis , linguistics , philosophy , genetics , computer security , biology

Suffix-trees are popular indexing structures for various sequence processing problems in biological data management. We investigate here the possibility of enhancing the search efficiency of disk-resident suffix-trees through customized layouts of tree-nodes to disk-pages. Specifically, we propose a new layout strategy, called Stellar, that provides significantly improved search performance on a representative set of real genomic sequences. Further, Stellar supports both the standard root-to-leaf lookup queries as well as sophisticated sequencesearch algorithms that exploit the suffix-links of suffix-trees. Our results are encouraging with regard to the ultimate objective of seamlessly integrating sequence processing in database engines.

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