Hidden Markov Models

Introduction to Hidden Markov Models and its Applications in Biology.- HMMs in Protein Fold Classification.- Application of Hidden Markov Models in Biomolecular Simulations.- Predicting Beta Barrel Transmembrane Proteins using HMMs.- Predicting Alpha Helical Transmembrane Proteins using HMMs.- Self-Organizing Hidden Markov Model Map (SOHMMM): Biological Sequence Clustering and Cluster Visualization.- Analyzing Single Molecule FRET Trajectories using HMM.- Modelling ChIP-seq Data using HMMs.- Hidden Markov Models in Bioinformatics: SNV Inference from Next Generation Sequence.- Computationally Tractable Multivariate HMM in Genome-wide Mapping Studies.- Hidden Markov Models in Population Genomics.- Differential Gene Expression (DEX) and Alternative Splicing Events (ASE) for Temporal Dynamic Processes using HMMs and Hierarchical Bayesian Modeling Approaches.- Finding RNA-Protein Interaction Sites using HMM.- Automated Estimation of Mouse Social Behaviours Based on a Hidden Markov Model.- Modeling Movement Primitives with Hidden Markov Models for Robotic and Biomedical Applications.