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@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}
}
TY - JOUR
ID - 972794
AU - Bystrý, Vojtěch - Lexa, Matej
PY - 2012
TI - cswHMM: a novel context switching hidden Markov model for biological sequence analysis
PB - SciTePress
CY - Neuveden
SN - 9789898425904
KW - bioinformatics
KW - data-mining
KW - hidden Markov models
UR - http://www.scitepress.org/DigitalLibrary/Link.aspx?paper=79973a8a-3ae3-40b8-adc8-625c0b5645a5
N2 - 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.
ER -
BYSTRÝ, Vojtěch and Matej LEXA. cswHMM: a novel context switching hidden Markov model for biological sequence analysis. In Jan Schier, Carlos Correia, Ana Fred and Hugo Gamboa. \textit{Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms.}. Neuveden: SciTePress, 2012. p.~208-213. ISBN~978-989-8425-90-4. doi:10.5220/0003780902080213.
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