As more genomes are sequenced, researchers are looking to bring their computations in line with the underlying biology. They are creating software that incorporates phylogenetics, the descriptions of evolutionary distance, into the field’s favorite computational tool, the hidden Markov model (HMM).

HMMs “describe a probability distribution over an infinite number of sequences,” says Sean Eddy, associate professor at Washington University and coauthor of the textbook, Biological Sequence Analysis: Probabilistic Models of Proteins and Nucleic Acids, who has dubbed HMMs “the Legos of computational sequence analysis.”