Models and Algorithms for Biomolecules and Molecular Networks
[Book]
1 online resource (263)
IEEE Press Series on Biomedical Engineering ;
30
Geometric Models of Protein Structure and Function Prediction -- Introduction -- Theory and Model -- Idealized Ball Model -- Surface Models of Proteins -- Geometric Constructs -- Topological Structures -- Metric Measurements -- Algorithm and Computation -- Applications -- Protein Packing -- Predicting Protein Functions from Structures -- Discussion and Summary -- References -- Exercises -- Scoring Functions for Predicting Structure and Binding of Proteins -- Introduction -- General Framework of Scoring Function and Potential Function -- Protein Representation and Descriptors -- Functional Form -- Deriving Parameters of Potential Functions -- Statistical Method -- Background -- Theoretical Model -- Miyazawa-Jernigan Contact Potential -- Distance-Dependent Potential Function -- Geometric Potential Functions -- Optimization Method -- Geometric Nature of Discrimination -- Optimal Linear Potential Function -- Optimal Nonlinear Potential Function -- Deriving Optimal Nonlinear Scoring Function -- Optimization Techniques -- Applications -- Protein Structure Prediction -- Protein-Protein Docking Prediction -- Protein Design -- Protein Stability and Binding Affinity -- Discussion and Summary -- Knowledge-Based Statistical Potential Functions -- Relationship of Knowledge-Based Energy Functions and Further Development -- Optimized Potential Function -- Data Dependency of Knowledge-Based Potentials -- References -- Exercises -- Sampling Techniques: Estimating Evolutionary Rates and Generating Molecular Structures -- Introduction -- Principles of Monte Carlo Sampling -- Estimation Through Sampling from Target Distribution -- Rejection Sampling -- Markov Chains and Metropolis Monte Carlo Sampling -- Properties of Markov Chains -- Markov Chain Monte Carlo Sampling -- Sequential Monte Carlo Sampling -- Importance Sampling -- Sequential Importance Sampling -- Resampling -- Applications -- Markov Chain Monte Carlo for Evolutionary Rate Estimation -- Sequentail Chain Growth Monte Carlo for Estimating Conformational Entropy of RNA Loops -- Discussion and Summary -- References -- Exercises -- Stochastic Molecular Networks -- Introduction -- Reaction System and Discrete Chemical Master Equation -- Direct Solution of Chemical Master Equation -- State Enumeration with Finite Buffer -- Generalization and Multi-Buffer dCME Method -- Calculation of Steady-State Probability Landscape -- Calculation of Dynamically Evolving Probability Landscape -- Methods for State Space Truncation for Simplification -- Quantifying and Controlling Errors from State Space Truncation -- Approximating Discrete Chemical Master Equation -- Continuous Chemical Master Equation -- Stochastic Differential Equation: Fokker-Planck Approach -- Stochastic Differential Equation: Langevin Approach -- Other Approximations -- Stochastic Simulation -- Reaction Probability -- Reaction Trajectory -- Probability of Reaction Trajectory -- Stochastic Simulation Algorithm -- Applications -- Probability Landscape of a Stochastic Toggle Switch -- Epigenetic Decision Network of Cellular Fate in Phage Lambda -- Discussions and Summary -- References -- Exercises -- Cellular Interaction Networks -- Basic Definitions and Graph-Theoretic Notions -- Topological Representation -- Dynamical Representation -- Topological Representation of Dynamical Models -- Boolean Interaction Networks -- Signal Transduction Networks -- Synthesizing Signal Transduction Networks -- Collecting Data for Network Synthesis -- Transitive Reduction and Pseudo-node Collapse -- Redundancy and Degeneracy of Networks -- Random Interaction Networks and Statistical Evaluations -- Reverse Engineering of Biological Networks -- Modular Response Analysis Approach -- Parsimonious Combinatorial Approaches -- Evaluation of Quality of the Reconstructed Network -- References -- Exercises -- Dynamical Systems and Interaction Networks -- Some Basic Control-Theoretic Concepts -- Discrete-Time Boolean Network Models -- Artificial Neural Network Models -- Computational Powers of ANNs -- Reverse Engineering of ANNs -- Applications of ANN Models in Studying Biological Networks -- Piecewise Linear Models -- Dynamics of PL Models -- Biological Application of PL Models -- Monotone Systems -- Definition of Monotonicity -- Combinatorial Characterizations and Measure of Monotonicity -- Algorithmic Issues in Computing the Degree of Monotonicity M -- References -- Exercises -- Case Study of Biological Models -- Segment Polarity Network Models -- Boolean Network Model -- Signal Transduction Network Model -- ABA-Induced Stomatal Closure Network -- Epidermal Growth Factor Receptor Signaling Network -- C. elegans Metabolic Network -- Network for T-Cell Survival and Death in Large Granular Lymphocyte Leukemia -- References -- Exercises