Multiple Sequence Alignment with Hidden Markov Models Learned by Random Drift…

Hidden Markov Models (HMMs) are powerful tools for multiple sequence alignment (MSA), which is known to be an NPcomplete and important problem in bioinformatics. Learning HMMs is a difficult task, and many meta-heuristic methods, including particle swarm optimization (PSO), have been used for that. In this paper, a new variant of PSO, called the random drift particle swarm optimization (RDPSO) …