Higher-order hidden markov models with applications to DNA sequences

Wai Ki Ching; Eric S. Fung; Michael K. Ng

doi:10.1007/978-3-540-45080-1_73

Higher-order hidden markov models with applications to DNA sequences

Wai Ki Ching^*
, Eric S. Fung
, Michael K. Ng

^*Corresponding author for this work

Department of Mathematics

Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

18 Citations (Scopus)

Abstract

Hidden Markov models (HMMs) have been applied to many real-world applications. Very often HMMs only deal with the first order transition probability distribution among the hidden states. In this paper we develop higher-order HMMs. We study the evaluation of the probability of a sequence of observations based on higher-order HMMs and determination of a best sequence of model states.

Original language	English
Title of host publication	Intelligent Data Engineering and Automated Learning
Subtitle of host publication	4th International Conference, IDEAL 2003 Hong Kong, China, March 21–23, 2003 Revised Papers
Editors	Jiming Liu, Yiu-ming Cheung, Hujun Yin
Publisher	Springer Berlin Heidelberg
Pages	535-539
Number of pages	5
Edition	1st
ISBN (Electronic)	9783540450801
ISBN (Print)	9783540405504
DOIs	https://doi.org/10.1007/978-3-540-45080-1_73
Publication status	Published - 29 Jul 2003
Event	4th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2003 - Hong Kong Convention and Exhibition Centre, Hong Kong, China Duration: 21 Mar 2003 → 23 Mar 2003 https://link.springer.com/book/10.1007/b11717 http://www.comp.hkbu.edu.hk/IDEAL2003/ (conference website) http://www.comp.hkbu.edu.hk/IDEAL2003/ (conference program)

Publication series

Name	Lecture Notes in Computer Science
Volume	2690
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Name	IDEAL: International Conference on Intelligent Data Engineering and Automated Learning

Conference

Conference	4th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2003
Country/Territory	China
City	Hong Kong
Period	21/03/03 → 23/03/03
Internet address	https://link.springer.com/book/10.1007/b11717 http://www.comp.hkbu.edu.hk/IDEAL2003/ (conference website) http://www.comp.hkbu.edu.hk/IDEAL2003/ (conference program)

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 9 Industry, Innovation, and Infrastructure

Access to Document

10.1007/978-3-540-45080-1_73

Cite this

Ching, W. K., Fung, E. S., & Ng, M. K. (2003). Higher-order hidden markov models with applications to DNA sequences. In J. Liu, Y. Cheung, & H. Yin (Eds.), Intelligent Data Engineering and Automated Learning: 4th International Conference, IDEAL 2003 Hong Kong, China, March 21–23, 2003 Revised Papers (1st ed., pp. 535-539). (Lecture Notes in Computer Science; Vol. 2690), (IDEAL: International Conference on Intelligent Data Engineering and Automated Learning). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-540-45080-1_73

Ching, Wai Ki ; Fung, Eric S. ; Ng, Michael K. / Higher-order hidden markov models with applications to DNA sequences. Intelligent Data Engineering and Automated Learning: 4th International Conference, IDEAL 2003 Hong Kong, China, March 21–23, 2003 Revised Papers. editor / Jiming Liu ; Yiu-ming Cheung ; Hujun Yin. 1st. ed. Springer Berlin Heidelberg, 2003. pp. 535-539 (Lecture Notes in Computer Science). (IDEAL: International Conference on Intelligent Data Engineering and Automated Learning).

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abstract = "Hidden Markov models (HMMs) have been applied to many real-world applications. Very often HMMs only deal with the first order transition probability distribution among the hidden states. In this paper we develop higher-order HMMs. We study the evaluation of the probability of a sequence of observations based on higher-order HMMs and determination of a best sequence of model states.",

author = "Ching, \{Wai Ki\} and Fung, \{Eric S.\} and Ng, \{Michael K.\}",

note = "supported in part by RGC Grant No. RGC Grant No. HKU 7126/02P, and HKU CRCG Grant Nos. 10203408, 10203501, 10203907, 10203919, 10204436. Publisher Copyright: {\textcopyright} Springer-Verlag Berlin Heidelberg 2003; 4th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2003 ; Conference date: 21-03-2003 Through 23-03-2003",

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editor = "Jiming Liu and Yiu-ming Cheung and Hujun Yin",

booktitle = "Intelligent Data Engineering and Automated Learning",

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Ching, WK, Fung, ES & Ng, MK 2003, Higher-order hidden markov models with applications to DNA sequences. in J Liu, Y Cheung & H Yin (eds), Intelligent Data Engineering and Automated Learning: 4th International Conference, IDEAL 2003 Hong Kong, China, March 21–23, 2003 Revised Papers. 1st edn, Lecture Notes in Computer Science, vol. 2690, IDEAL: International Conference on Intelligent Data Engineering and Automated Learning, Springer Berlin Heidelberg, pp. 535-539, 4th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2003, Hong Kong, China, 21/03/03. https://doi.org/10.1007/978-3-540-45080-1_73

Higher-order hidden markov models with applications to DNA sequences. / Ching, Wai Ki; Fung, Eric S.; Ng, Michael K.
Intelligent Data Engineering and Automated Learning: 4th International Conference, IDEAL 2003 Hong Kong, China, March 21–23, 2003 Revised Papers. ed. / Jiming Liu; Yiu-ming Cheung; Hujun Yin. 1st. ed. Springer Berlin Heidelberg, 2003. p. 535-539 (Lecture Notes in Computer Science; Vol. 2690), (IDEAL: International Conference on Intelligent Data Engineering and Automated Learning).

Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

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T1 - Higher-order hidden markov models with applications to DNA sequences

AU - Ching, Wai Ki

AU - Fung, Eric S.

AU - Ng, Michael K.

N1 - supported in part by RGC Grant No. RGC Grant No. HKU 7126/02P, and HKU CRCG Grant Nos. 10203408, 10203501, 10203907, 10203919, 10204436. Publisher Copyright: © Springer-Verlag Berlin Heidelberg 2003

PY - 2003/7/29

Y1 - 2003/7/29

N2 - Hidden Markov models (HMMs) have been applied to many real-world applications. Very often HMMs only deal with the first order transition probability distribution among the hidden states. In this paper we develop higher-order HMMs. We study the evaluation of the probability of a sequence of observations based on higher-order HMMs and determination of a best sequence of model states.

AB - Hidden Markov models (HMMs) have been applied to many real-world applications. Very often HMMs only deal with the first order transition probability distribution among the hidden states. In this paper we develop higher-order HMMs. We study the evaluation of the probability of a sequence of observations based on higher-order HMMs and determination of a best sequence of model states.

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BT - Intelligent Data Engineering and Automated Learning

A2 - Liu, Jiming

A2 - Cheung, Yiu-ming

A2 - Yin, Hujun

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Ching WK, Fung ES, Ng MK. Higher-order hidden markov models with applications to DNA sequences. In Liu J, Cheung Y, Yin H, editors, Intelligent Data Engineering and Automated Learning: 4th International Conference, IDEAL 2003 Hong Kong, China, March 21–23, 2003 Revised Papers. 1st ed. Springer Berlin Heidelberg. 2003. p. 535-539. (Lecture Notes in Computer Science). (IDEAL: International Conference on Intelligent Data Engineering and Automated Learning). doi: 10.1007/978-3-540-45080-1_73

Higher-order hidden markov models with applications to DNA sequences

Abstract

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Conference

UN SDGs

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