A sequence database consists of sequences of ordered elements or events, recorded with or without a concrete notion of time. There are many applications involving sequence data. Typical examples include customer shopping sequences, Web clickstreams, bio- logical sequences, sequences of events in science and engineering, and in natural and social developments. In this section, we study sequential pattern mining in transactional databases. In particular, we start with the basic concepts of sequential pattern mining in Section 8.3.1. Section 8.3.2 presents several scalable methods for such mining. Constraint-based sequential pattern mining is described in Section 8.3.3. Periodicity analysis for sequence data is discussed in Section 8.3.4. Specific methods for mining sequence patterns in biological data are addressed in Section 8.4.