隠れマルコフモデルが明かす生物配列の情報

抄録

Biological sequence analysis based on hidden Markov models (HMMs) is no doubt one of the most successful endeavors in the field of bioninformatics. HMMs are widely used not only for motif search but also for gene finding and protein fold recognition nowadays. Compared with existing models, HMMs possess flexibility to describe complex structures of sequence information. Moreover, various kinds of computer algorithms based on HMMs which enable us to model and interpret biological sequence data have been developed. In this paper, we introduce recent research topics of biological sequence analysis using HMMs and discuss a future perspective of the research.