TY - BOOK UR - http://lib.ugent.be/catalog/ebk01:3710000000204272 ID - ebk01:3710000000204272 LA - eng TI - Hidden Markov Processes : Theory and Applications to Biology PY - 2014 SN - 9781400850518 AU - Vidyasagar, M., author. AB - This book explores important aspects of Markov and hidden Markov processes and the applications of these ideas to various problems in computational biology. The book starts from first principles, so that no previous knowledge of probability is necessary. However, the work is rigorous and mathematical, making it useful to engineers and mathematicians, even those not interested in biological applications. A range of exercises is provided, including drills to familiarize the reader with concepts and more advanced problems that require deep thinking about the theory. Biological applications are taken from post-genomic biology, especially genomics and proteomics. The topics examined include standard material such as the Perron-Frobenius theorem, transient and recurrent states, hitting probabilities and hitting times, maximum likelihood estimation, the Viterbi algorithm, and the Baum-Welch algorithm. The book contains discussions of extremely useful topics not usually seen at the basic level, such as ergodicity of Markov processes, Markov Chain Monte Carlo (MCMC), information theory, and large deviation theory for both i.i.d and Markov processes. The book also presents state-of-the-art realization theory for hidden Markov models. Among biological applications, it offers an in-depth look at the BLAST (Basic Local Alignment Search Technique) algorithm, including a comprehensive explanation of the underlying theory. Other applications such as profile hidden Markov models are also explored. ER -Download RIS file
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020 | a 9781400850518 | ||
024 | 7 | a 10.1515/9781400850518 2 doi | |
035 | a (DE-B1597)447402 | ||
035 | a (OCoLC)885122066 | ||
035 | a (OCoLC)888550795 | ||
040 | a IN-ChSCO b eng c IN-ChSCO e rda | ||
041 | a eng | ||
050 | 4 | a QH324.2 b .V54 2014 | |
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100 | 1 | a Vidyasagar, M., e author. | |
245 | 1 | a Hidden Markov Processes : b Theory and Applications to Biology / c M. Vidyasagar. | |
264 | 1 | a Princeton, N.J. : b Princeton University Press, c [2014]. | |
264 | 4 | c Â©2014. | |
300 | a 1 online resource(312p.) : b illustrations. | ||
336 | a text 2 rdacontent | ||
337 | a computer 2 rdamedia | ||
338 | a online resource 2 rdacarrier | ||
347 | a text file b PDF 2 rda | ||
490 | a Princeton Series in Applied Mathematics | ||
505 | t Frontmatter -- t Contents -- t Preface -- t PART 1. Preliminaries -- t Chapter One. Introduction to Probability and Random Variables -- t Chapter Two. Introduction to Information Theory -- t Chapter Three. Nonnegative Matrices -- t PART 2. Hidden Markov Processes -- t Chapter Four. Markov Processes -- t Chapter Five. Introduction to Large Deviation Theory -- t Chapter Six. Hidden Markov Processes: Basic Properties -- t Chapter Seven. Hidden Markov Processes: The Complete Realization Problem -- t PART 3. Applications to Biology -- t Chapter Eight. Some Applications to Computational Biology -- t Chapter Nine. BLAST Theory -- t Bibliography -- t Index -- t Backmatter | ||
520 | a This book explores important aspects of Markov and hidden Markov processes and the applications of these ideas to various problems in computational biology. The book starts from first principles, so that no previous knowledge of probability is necessary. However, the work is rigorous and mathematical, making it useful to engineers and mathematicians, even those not interested in biological applications. A range of exercises is provided, including drills to familiarize the reader with concepts and more advanced problems that require deep thinking about the theory. Biological applications are taken from post-genomic biology, especially genomics and proteomics. The topics examined include standard material such as the Perron-Frobenius theorem, transient and recurrent states, hitting probabilities and hitting times, maximum likelihood estimation, the Viterbi algorithm, and the Baum-Welch algorithm. The book contains discussions of extremely useful topics not usually seen at the basic level, such as ergodicity of Markov processes, Markov Chain Monte Carlo (MCMC), information theory, and large deviation theory for both i.i.d and Markov processes. The book also presents state-of-the-art realization theory for hidden Markov models. Among biological applications, it offers an in-depth look at the BLAST (Basic Local Alignment Search Technique) algorithm, including a comprehensive explanation of the underlying theory. Other applications such as profile hidden Markov models are also explored. | ||
533 | a Electronic reproduction. b Princeton, N.J. : c Princeton University Press, d 2014. n Mode of access: World Wide Web. n System requirements: Web browser. n Access may be restricted to users at subscribing institutions. | ||
538 | a Mode of access: Internet via World Wide Web. | ||
545 | a VidyasagarM.: M. Vidyasagar is the Cecil and Ida Green Chair in Systems Biology Science at the University of Texas, Dallas. His many books include "Computational Cancer Biology: An Interaction Network Approach" and "Control System Synthesis: A Factorization Approach". | ||
546 | a In English. | ||
588 | a Description based on online resource; title from PDF title page (publisherâ€™s Web site, viewed March 24, 2015) | ||
650 | a Computational biology. | ||
650 | a Electronic books. | ||
650 | a Markov processes. | ||
650 | 4 | a Biology. | |
650 | 4 | a Computational biology. | |
650 | 4 | a Markov processes. | |
650 | 4 | a Mathematics. | |
650 | 4 | a Probability and Statistics. | |
650 | 4 | a Stochastic processes. | |
650 | 7 | a Mathematik. | |
773 | 8 | i Title is part of eBook package: d De Gruyter t Princeton eBook Package 2014-2015 z 978-3-11-044251-9 | |
773 | 8 | i Title is part of eBook package: d De Gruyter t Princeton eBook Package Backlist 2000-2014 z 978-3-11-045953-1 | |
773 | 8 | i Title is part of eBook package: d De Gruyter t Princeton Series in Applied Mathematics ebook package z 978-3-11-051583-1 | |
773 | 8 | i Title is part of eBook package: d De Gruyter t Princeton Univ. Press eBook Package 2014 z 978-3-11-041342-7 | |
856 | 4 | u https://doi.org/10.1515/9781400850518 | |
856 | 4 | 2 | 3 Cover u https://www.degruyter.com/doc/cover/9781400850518.jpg |
912 | a 978-3-11-041342-7 Princeton Univ. Press eBook Package 2014 | ||
912 | a 978-3-11-044251-9 Princeton eBook Package Frontlist 2014-2015 | ||
912 | a 978-3-11-045953-1 Princeton eBook Package Backlist 2000-2014 | ||
912 | a 978-3-11-051583-1 Princeton Series in Applied Mathematics ebook package | ||
912 | a GBV-deGruyter-alles | ||
912 | a GBV-deGruyter-PDA12STME | ||
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