ABSTRACT
In recent years the volume of biological data has increased exponentially. Concomitantly, the speed with which such data is generated has increased as well. It is now possible to sequence a bacterial genome in a single day. Thus efficient data structures are needed to archive and retrieve biological data. Furthermore, this explosion of data has increased the need to analyze a large amount of data in a reasonable time. With the availability of complete genomes, researchers have begun to compare whole genomes [4, 11, 26, 27]. This further increases the scale of problems addressed, and algorithms that worked well for smaller scale problems are either insufficient or inappropriate. For example, dynamic programming techniques worked well to identify the matching regions between two genes. However, heuristics must be applied when we try to identify highly conserved regions between two genomes in reasonable time and space. Suffix trees can serve as an efficient data structure to analyze DNA and protein sequences. They can also be used to provide exact matches efficiently, which many heuristics depend on.
