Analysis of Combinatorial Gene Regulation with Thermodynamic Models -- RNA Secondary Structure Prediction and Gene Regulation by Small RNAs -- Some Critical Data Quality Control Issues of Oligoarrays -- Stochastic-Process Approach to Nonequilibrium Thermodynamics and Biological Signal Transduction -- Granger Causality: Theory and Applications -- Transcription Factor Binding Site Identification by Phylogenetic Footprinting -- Learning Network from High-Dimensional Array Data -- Computational Methods for Predicting Domain–Domain Interactions -- Irreversible Stochastic Processes, Coupled Diffusions and Systems Biochemistry -- Probability Modeling and Statistical Inference in Periodic Cancer Screening -- On Construction of the Smallest One-sided Confidence Intervals and Its Application in Identifying the Minimum Effective Dose -- Group Variable Selection Methods and Their Applications in Analysis of Genomic Data -- Modeling Protein-Signaling Networks with Granger Causality Test -- DNA Copy Number Profiling in Normal and Tumor Genomes -- Spatial Disease Surveillance: Methods and Applications -- From QTL Mapping to eQTL Analysis -- An Evaluation of Gene Module Concepts in the Interpretation of Gene Expression Data -- Readout of Spike Waves in a Microcolumn -- False Positive Control for Genome-Wide ChIP-Chip Tiling Arrays.

Biological and biomedical studies have entered a new era due to the widespread use of mathematical models and computational approaches. What was no more than a theoretician's fantasy 20 years ago has become the blooming field of computational biology. Furthermore, this powerful and stimulating research paradigm in biological studies has in turn led to new developments in mathematics, physics and computer science. This unique volume surveys state-of-the-art research on statistical methods in molecular and systems biology, with contributions from leading experts in the field. Each chapter discusses theoretical aspects, applications to biological problems, and possible future developments. Understanding the biology at a molecular and system level stands among the most exciting challenges faced by modern science. This text clearly demonstrates how computational and mathematical approaches continue to address this challenge. Topics and features: Presents the use of thermodynamic models to analyze gene regulatory mechanisms Reviews major algorithms for RNA secondary structure prediction, with a focus on ensemble-based approaches Discusses how developments in the area of oligo arrays has led to a better understanding of the array mechanism and improvements in microarray data analysis Examines the application of models of stochastic processes in nonequilibrium thermodynamics and biological signal transduction Describes phylogenetic footprinting methods for TFBS identification, based on alignments Introduces penalized regression-based methods for constructing genetic interaction or regulatory networks Investigates the specific role played by irreversible Markov processes in modeling cellular biochemical systems Explores the concept of gene modules in a transcriptional regulatory network With reviews of current hot topics in computational biology and systems biology, supplied by an international selection of top researchers, this is an essential text for researchers and graduate students in computational biology, biology and mathematics.