Search-Optimized Suffix-Tree Storage for Biological Applications

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.