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Hidden Markov Models

Overview of attention for book
Hidden Markov Models
Springer New York

Table of Contents

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    Book Overview
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    Chapter 1 Introduction to Hidden Markov Models and Its Applications in Biology
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    Chapter 2 HMMs in Protein Fold Classification
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    Chapter 3 Application of Hidden Markov Models in Biomolecular Simulations
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    Chapter 4 Predicting Beta Barrel Transmembrane Proteins Using HMMs
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    Chapter 5 Predicting Alpha Helical Transmembrane Proteins Using HMMs
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    Chapter 6 Self-Organizing Hidden Markov Model Map (SOHMMM): Biological Sequence Clustering and Cluster Visualization
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    Chapter 7 Analyzing Single Molecule FRET Trajectories Using HMM
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    Chapter 8 Modelling ChIP-seq Data Using HMMs
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    Chapter 9 Hidden Markov Models in Bioinformatics: SNV Inference from Next Generation Sequence
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    Chapter 10 Computationally Tractable Multivariate HMM in Genome-Wide Mapping Studies
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    Chapter 11 Hidden Markov Models in Population Genomics
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    Chapter 12 Differential Gene Expression (DEX) and Alternative Splicing Events (ASE) for Temporal Dynamic Processes Using HMMs and Hierarchical Bayesian Modeling Approaches
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    Chapter 13 Finding RNA–Protein Interaction Sites Using HMMs
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    Chapter 14 Automated Estimation of Mouse Social Behaviors Based on a Hidden Markov Model
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    Chapter 15 Modeling Movement Primitives with Hidden Markov Models for Robotic and Biomedical Applications
Attention for Chapter 11: Hidden Markov Models in Population Genomics
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