In the last years, the information stored in biological data-sets grew up exponentially, and new methods and tools have been proposed to interpret and retrieve useful information from such data. Most biological data-sets contain biological sequences (e.g., DNA and protein sequences). Thus, it is much significant to have techniques available capable of mining patterns from such sequences to discover interesting information from them. For instance, singling out for common or similar sub-sequences in sets of bio-sequences is sensible as these are usually associated to similar biological functions expressed by the corresponding macromolecules. The aim of this chapter is to explain how pattern discovery can be applied to deal with such important biological problems, describing also a number of relevant techniques proposed in the literature. A simple formalization of the problem is given and specialized for each of the presented approaches. Such a formalization should ease reading and understanding the illustrated material by providing a simple-to-follow roadmap scheme through the diverse methods for pattern extraction we are going to illustrate.