Hidden Markov Models with Applications in Computational Biology

Name: Hidden Markov Models with Applications in Computational Biology
Brand: Sudwestdeutscher Verlag Fur Hochschulschriften AG
SKU: 9783838136042
Price: 298.3 PLN
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Model Extensions and Advanced Analysis of DNA Microarray Data

Autor: Michael Seifert

Język:

Oprawa: Miękka

Wydawca: Sudwestdeutscher Verlag Fur Hochschulschriften AG

Dostępność: Dostępna u dostawcy

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Standard first-order Hidden Markov Models (HMMs) are very popular tools for the analysis of sequenti...

Informacje o książce

Autor

Michael Seifert

Język

Angielski

Oprawa

Książka - Miękka

Data wydania

2013

strony

184

EAN

9783838136042

ISBN

3838136047

Enbook ID

07088039

Wydawca

Sudwestdeutscher Verlag Fur Hochschulschriften AG

Waga

277

Wymiary

152 x 229 x 11

Pełny opis

Standard first-order Hidden Markov Models (HMMs) are very popular tools for the analysis of sequential data in applied sciences. HMMs are versatile and structurally simple models enabling probabilistic modeling based on a sound theoretical grounding. In contrast to the broad usage of first-order HMMs, applications of higher-order HMMs are very rare, but they have been proven to be powerful extensions of first-order HMMs including applications in speech recognition, image segmentation or computational biology. This book provides the first easily accessible and comprehensive extension of the algorithmic basics of first-order HMMs to higher-order HMMs coupled with practical applications in computational biology. The book starts with a theoretical part developing the algorithmic basics of higher-order HMMs and two novel model extensions (i) parsimonious higher-order HMMs and (ii) HMMs with scaled transition matrices. The second part considers applications of these models to the analysis of different DNA microarray data sets followed by a detailed discussion. The book addresses readers having basic knowledge on first-order HMMs interested to gain more insights on higher-order HMMs.

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Hidden Markov Models with Applications in Computational Biology

Model Extensions and Advanced Analysis of DNA Microarray Data

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