cswHMM: a novel context switching hidden Markov model for biological sequence analysis

Varování

Publikace nespadá pod Fakultu sportovních studií, ale pod Fakultu informatiky. Oficiální stránka publikace je na webu muni.cz.
Autoři

BYSTRÝ Vojtěch LEXA Matej

Rok publikování 2012
Druh Článek ve sborníku
Konference Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms.
Fakulta / Pracoviště MU

Fakulta informatiky

Citace
www http://www.scitepress.org/DigitalLibrary/Link.aspx?paper=79973a8a-3ae3-40b8-adc8-625c0b5645a5
Doi http://dx.doi.org/10.5220/0003780902080213
Obor Informatika
Klíčová slova bioinformatics; data-mining; hidden Markov models
Přiložené soubory
Popis 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.
Související projekty:

Používáte starou verzi internetového prohlížeče. Doporučujeme aktualizovat Váš prohlížeč na nejnovější verzi.

Další info