Publication details

 

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

Basic information
Original title:cswHMM: a novel context switching hidden Markov model for biological sequence analysis
Authors:Vojtěch Bystrý, Matej Lexa
Further information
Citation:BYSTRÝ, Vojtěch a Matej LEXA. cswHMM: a novel context switching hidden Markov model for biological sequence analysis. In Jan Schier, Carlos Correia, Ana Fred and Hugo Gamboa. Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms. Neuveden: SciTePress, 2012. s. 208-213, 6 s. ISBN 978-989-8425-90-4. doi:10.5220/0003780902080213.Export BibTeX
@inproceedings{972794,
author = {Bystrý, Vojtěch and Lexa, Matej},
address = {Neuveden},
booktitle = {Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms.},
doi = {http://dx.doi.org/10.5220/0003780902080213},
editor = {Jan Schier, Carlos Correia, Ana Fred and Hugo Gamboa},
keywords = {bioinformatics; data-mining; hidden Markov models},
howpublished = {tištěná verze "print"},
language = {eng},
location = {Neuveden},
isbn = {978-989-8425-90-4},
pages = {208-213},
publisher = {SciTePress},
title = {cswHMM: a novel context switching hidden Markov model for biological sequence analysis},
url = {http://www.scitepress.org/DigitalLibrary/Link.aspx?paper=79973a8a-3ae3-40b8-adc8-625c0b5645a5},
year = {2012}
}
Original language:English
Field:Informatics
WWW:link to a new windowhttp://www.scitepress.org/DigitalLibrary/Link.aspx?paper=79973a8a-3ae3-40b8-adc8-625c0b5645a5
Type:Article in Proceedings
Keywords:bioinformatics; data-mining; hidden Markov models
Attached files:link to a new window37809.pdf

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.

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