Suffix trees (and relatives) come of age in bioinformatics

Summary form only given. In the past, several things limited the wider application of suffix trees: large memory requirements; limited locality of reference; the conceptual difficulty of the algorithms; and lack of available code; lack of general exposure in the bioinformatics community (and even the computer science community) to suffix trees. Much has changed since 1997. Suffix trees and close relatives are now widely taught in graduate level courses on computer algorithms and on bioinformatics; there are several good expositions on suffix tree algorithms and uses; the space requirements have been substantially reduced; machine memories have greatly increased; additional variants of suffix trees have been introduced that address some of their deficiencies; and suffix tree code is publicly available. As a result, and to some extent as a cause, there are now many more applications in bioinformatics of suffix trees and related data structures. The author addresses the wider uses of suffix trees in bioinformatics.