The vast increase of data in biology has meant that many aspects of computational science have been drawn into the field. Two areas of crucial importance are large-scale data management and machine learning. The field between computational science and biology is varyingly described as “computational biology” or “bioinformatics.” This paper reviews machine learning techniques based on the use of hidden Markov models (HMMs) for investigating biomolecular sequences. The approach is illustrated with brief descriptions of gene-prediction HMMs and protein family HMMs.