cswHMM: a novel context switching hidden Markov model for biological sequence analysis
|Original title:||cswHMM: a novel context switching hidden Markov model for biological sequence analysis|
|Authors:||Vojtěch Bystrý, Matej Lexa|
In this work we created a sequence model that goes beyond simple linear patterns to model a specific type of higher-order relationship possible in biological sequences. Particularly, we seek models that can account for partially overlaid and interleaved patterns in biological sequences. Our proposed context-switching model (cswHMM) is designed as a variable-order hidden Markov model (HMM) with a specific structure that allows switching control between two or more sub-models.Tests of this approach suggest that a combination of HMMs for protein sequence analysis, such as pattern mining based HMMs or profile HMMs, with the context-switching approach can improve the descriptive ability and performance of the models.