Hidden Markov Models, 1st ed. 2017 Methods and Protocols Methods in Molecular Biology Series, Vol. 1552

This volume aims to provide a new perspective on the broader usage of Hidden Markov Models (HMMs) in biology. Hidden Markov Models: Methods and Protocols guides readers through chapters on biological systems; ranging from single biomolecule, cellular level, and to organism level and the use of HMMs in unravelling the complex mechanisms that govern these complex systems.  Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls.

Authoritative and practical, Hidden Markov Models: Methods and Protocols aims to demonstrate the impact of HMM in biology and inspire new research.

1. Introduction to Hidden Markov Models and its Applications in Biology

M S Vijayabaskar

2. HMMs in Protein Fold Classification

Christos Lampros, Costas Papaloukas, Themis Exarchos, and Dimitrios I. Fotiadis

3. Application of Hidden Markov Models in Biomolecular Simulations

Saurabh Shukla, Zahra Shamsi, Alexander S. Moffett, Balaji Selvam, and Diwakar Shukla

4. Predicting Beta Barrel Transmembrane Proteins using HMMs

Georgios N. Tsaousis, Stavros J. Hamodrakas, and Pantelis G. Bagos

5. Predicting Alpha Helical Transmembrane Proteins using HMMs

Georgios N. Tsaousis, Margarita C. Theodoropoulou, Stavros J. Hamodrakas, and Pantelis G. Bagos

6. Self-Organizing Hidden Markov Model Map (SOHMMM): Biological Sequence Clustering and Cluster Visualization

Christos Ferles, William-Scott Beaufort, and Vanessa Ferle

7. Analyzing Single Molecule FRET Trajectories using HMM

Kenji Okamoto

8. Modelling ChIP-seq Data using HMMs

9. Hidden Markov Models in Bioinformatics: SNV Inference from Next Generation Sequence

Jiawen Bianand Xiaobo Zhou

10. Computationally Tractable Multivariate HMM in Genome-wide Mapping Studies

Hyungwon Choi, Debashis Ghosh, and Zhaohui Qin

Julien Y. Dutheil

12. Differential Gene Expression (DEX) and Alternative Splicing Events (ASE) for Temporal Dynamic Processes using HMMs and Hierarchical Bayesian Modeling Approaches

Sunghee Oh and Seongho Song

13. Finding RNA-Protein Interaction Sites using HMM

Tao Wang, Jonghyun Yun, Yang Xie, and Guanghua Xiao

14. Automated Estimation of Mouse Social Behaviours Based on a Hidden Markov Model

Toshiya Arakawa, Akira Tanave, Aki Takahashi, Satoshi Kakihara, Tsuyoshi Koide, and Takashi Tsuchiya

15. Modeling Movement Primitives with Hidden Markov Models for Robotic and Biomedical Applications

Michelle Karg and Dana Kulić

Includes cutting-edge methods and protocols

Provides step-by-step detail essential for reproducible results

Contains key notes and implementation advice from the experts

Includes supplementary material: sn.pub/extras