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Hidden Markov processes : theory and applications to biology / / M. Vidyasagar



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Autore: Vidyasagar M (Mathukumalli), <1947-> Visualizza persona
Titolo: Hidden Markov processes : theory and applications to biology / / M. Vidyasagar Visualizza cluster
Pubblicazione: Princeton, New Jersey ; ; Oxford, England : , : Princeton University Press, , 2014
©2014
Edizione: Course Book
Descrizione fisica: 1 online resource (303 p.)
Disciplina: 570.285
Soggetto topico: Computational biology
Markov processes
Soggetto non controllato: BLAST theory
BaumЗelch algorithm
Bayes' rule
Cramr's theorem
GENSCAN algorithm
GLIMMER algorithm
Hankel matrix
Hankel rank condition
Hoeffding's inequality
KullbackЌeibler divergence
Markov chain
Markov process
Markov property
Monte Carlo simulation
PerronІrobenius theorem
Probability theory
Sanov's theorem
Viterbi algorithm
alignment
alpha-mixing process
amino acids
canonical form
complete realization problem
computational biology
concave function
conditional entropy
convex function
entropy function
entropy
ergodicity
expected value
finite alphabet
gene-finding problem
genomics
hidden Markov model
hidden Markov processes
hitting probability
information theory
irreducible matrices
large deviation property
large deviation theory
likelihood estimation
likelihood
lower semi-continuous function
lower semi-continuous relaxation
maximal segmental score
maximum likelihood estimate
mean hitting time
moment generating function
nonnegative matrices
nucleotide
optimal gapped alignment
periodic irreducible matrices
post-genomic biology
primitive matrices
probability distribution
probability
protein classification
proteomics
quasi-realization
random variable
rate function
recurrent state
relative entropy rate
relative entropy
sequence alignment
sequence
state transition matrix
stationary distribution
total variation distance
transient state
ultra-mixing process
Classificazione: SK 820
Note generali: Description based upon print version of record.
Nota di bibliografia: Includes bibliographical references and index.
Nota di contenuto: Front matter -- Contents -- Preface -- PART 1. Preliminaries -- Chapter One. Introduction to Probability and Random Variables -- Chapter Two. Introduction to Information Theory -- Chapter Three. Nonnegative Matrices -- PART 2. Hidden Markov Processes -- Chapter Four. Markov Processes -- Chapter Five. Introduction to Large Deviation Theory -- Chapter Six. Hidden Markov Processes: Basic Properties -- Chapter Seven. Hidden Markov Processes: The Complete Realization Problem -- PART 3. Applications to Biology -- Chapter Eight. Some Applications to Computational Biology -- Chapter Nine. BLAST Theory -- Bibliography -- Index -- Back matter
Sommario/riassunto: 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.
Titolo autorizzato: Hidden Markov processes  Visualizza cluster
ISBN: 1-4008-5051-7
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 9910786777403321
Lo trovi qui: Univ. Federico II
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Serie: Princeton series in applied mathematics.