Analysing the content of a biological sequence can often be modeled as a segmentation problem. For example, one may wish to segment a genome in coding and non-coding regions, where only the former are translated to proteins. Statistical features of what genes usually look like can be used to derive an optimization framework. This process can be formalized through hidden Markov models, and the underlying segmentation problem can be solved using dynamic programming. This chapter introduces the key methods related to such optimization.