The Resource Hidden Markov processes : theory and applications to biology, M. Vidyasagar
Hidden Markov processes : theory and applications to biology, M. Vidyasagar
 Summary
 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 postgenomic biology, especially genomics and proteomics. The topics examined include standard material such as the PerronFrobenius theorem, transient and recurrent states, hitting probabilities and hitting times, maximum likelihood estimation, the Viterbi algorithm, and the BaumWelch 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 stateoftheart realization theory for hidden Markov models. Among biological applications, it offers an indepth 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
 Language
 eng
 Extent
 1 online resource (xiv, 287 pages).
 Contents

 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
 Backmatter
 Frontmatter
 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
 Isbn
 9781400850518
 Label
 Hidden Markov processes : theory and applications to biology
 Title
 Hidden Markov processes
 Title remainder
 theory and applications to biology
 Statement of responsibility
 M. Vidyasagar
 Language
 eng
 Summary
 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 postgenomic biology, especially genomics and proteomics. The topics examined include standard material such as the PerronFrobenius theorem, transient and recurrent states, hitting probabilities and hitting times, maximum likelihood estimation, the Viterbi algorithm, and the BaumWelch 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 stateoftheart realization theory for hidden Markov models. Among biological applications, it offers an indepth 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
 Cataloging source
 YDXCP
 Index
 index present
 Language note
 In English
 Literary form
 non fiction
 Nature of contents

 dictionaries
 bibliography
 Series statement
 Princeton series in applied mathematics
 Label
 Hidden Markov processes : theory and applications to biology, M. Vidyasagar
 Bibliography note
 Includes bibliographical references and index
 Carrier category
 online resource
 Carrier category code
 cr
 Carrier MARC source
 rdacarrier
 Content category
 text
 Content type code
 txt
 Content type MARC source
 rdacontent
 Contents

 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
 Backmatter
 Frontmatter
 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
 http://library.link/vocab/cover_art
 https://contentcafe2.btol.com/ContentCafe/Jacket.aspx?Return=1&Type=S&Value=9781400850518&userID=ebscotest&password=ebscotest
 Dimensions
 unknown
 http://library.link/vocab/discovery_link
 {'f': 'http://opac.lib.rpi.edu/record=b4332070'}
 Extent
 1 online resource (xiv, 287 pages).
 Form of item
 online
 Isbn
 9781400850518
 Lccn
 2014009277
 Media category
 computer
 Media MARC source
 rdamedia
 Media type code
 c
 Specific material designation
 remote
Embed (Experimental)
Settings
Select options that apply then copy and paste the RDF/HTML data fragment to include in your application
Embed this data in a secure (HTTPS) page:
Layout options:
Include data citation:
<div class="citation" vocab="http://schema.org/"><i class="fa faexternallinksquare fafw"></i> Data from <span resource="http://link.lib.rpi.edu/portal/HiddenMarkovprocessestheoryandapplications/utX0Iw4WDns/" typeof="WorkExample http://bibfra.me/vocab/lite/Item"><span property="name http://bibfra.me/vocab/lite/label"><a href="http://link.lib.rpi.edu/portal/HiddenMarkovprocessestheoryandapplications/utX0Iw4WDns/">Hidden Markov processes : theory and applications to biology, M. Vidyasagar</a></span>  <span property="offers" typeOf="Offer"><span property="offeredBy" typeof="Library ll:Library" resource="http://link.lib.rpi.edu/"><span property="name http://bibfra.me/vocab/lite/label"><a property="url" href="http://link.lib.rpi.edu/">Rensselaer Libraries</a></span></span></span></span></div>
Note: Adjust the width and height settings defined in the RDF/HTML code fragment to best match your requirements
Preview
Cite Data  Experimental
Data Citation of the Item Hidden Markov processes : theory and applications to biology, M. Vidyasagar
Copy and paste the following RDF/HTML data fragment to cite this resource
<div class="citation" vocab="http://schema.org/"><i class="fa faexternallinksquare fafw"></i> Data from <span resource="http://link.lib.rpi.edu/portal/HiddenMarkovprocessestheoryandapplications/utX0Iw4WDns/" typeof="WorkExample http://bibfra.me/vocab/lite/Item"><span property="name http://bibfra.me/vocab/lite/label"><a href="http://link.lib.rpi.edu/portal/HiddenMarkovprocessestheoryandapplications/utX0Iw4WDns/">Hidden Markov processes : theory and applications to biology, M. Vidyasagar</a></span>  <span property="offers" typeOf="Offer"><span property="offeredBy" typeof="Library ll:Library" resource="http://link.lib.rpi.edu/"><span property="name http://bibfra.me/vocab/lite/label"><a property="url" href="http://link.lib.rpi.edu/">Rensselaer Libraries</a></span></span></span></span></div>