Frontiers in Computational and Systems Biology [the conference from which this book results was to celebrate the 70th birthday of Qian MinPing, a Professor in Mathematics and Theoretical Biology at Peking University

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. Front Matter....Pages I-XXV Analysis of Combinatorial Gene Regulation with Thermodynamic Models....Pages 1-17 RNA Secondary Structure Prediction and Gene Regulation by Small RNAs....Pages 19-37 Some Critical Data Quality Control Issues of Oligoarrays....Pages 39-59 Stochastic-Process Approach to Nonequilibrium Thermodynamics and Biological Signal Transduction....Pages 61-81 Granger Causality: Theory and Applications....Pages 83-111 Transcription Factor Binding Site Identification by Phylogenetic Footprinting....Pages 113-131 Learning Network from High-Dimensional Array Data....Pages 133-156 Computational Methods for Predicting Domain–Domain Interactions....Pages 157-173 Irreversible Stochastic Processes, Coupled Diffusions and Systems Biochemistry....Pages 175-201 Probability Modeling and Statistical Inference in Periodic Cancer Screening....Pages 203-218 On Construction of the Smallest One-sided Confidence Intervals and Its Application in Identifying the Minimum Effective Dose....Pages 219-230 Group Variable Selection Methods and Their Applications in Analysis of Genomic Data....Pages 231-248 Modeling Protein-Signaling Networks with Granger Causality Test....Pages 249-257 DNA Copy Number Profiling in Normal and Tumor Genomes....Pages 259-281 Spatial Disease Surveillance: Methods and Applications....Pages 283-300 From QTL Mapping to eQTL Analysis....Pages 301-329 An Evaluation of Gene Module Concepts in the Interpretation of Gene Expression Data....Pages 331-349 Readout of Spike Waves in a Microcolumn....Pages 351-369 False Positive Control for Genome-Wide ChIP-Chip Tiling Arrays....Pages 371-381 Back Matter....Pages 383-401 Biological and biomedical studies have entered a new era over the past two decades thanks to the wide use of mathematical models and computational approaches. A booming of computational biology, which sheerly was a theoretician’s fantasy twenty years ago, has become a reality. Obsession with computational biology and theoretical approaches is evidenced in articles hailing the arrival of what are va- ously called quantitative biology, bioinformatics, theoretical biology, and systems biology. New technologies and data resources in genetics, such as the International HapMap project, enable large-scale studies, such as genome-wide association st- ies, which could potentially identify most common genetic variants as well as rare variants of the human DNA that may alter individual’s susceptibility to disease and the response to medical treatment. Meanwhile the multi-electrode recording from behaving animals makes it feasible to control the animal mental activity, which could potentially lead to the development of useful brain–machine interfaces. - bracing the sheer volume of genetic, genomic, and other type of data, an essential approach is, ?rst of all, to avoid drowning the true signal in the data. It has been witnessed that theoretical approach to biology has emerged as a powerful and st- ulating research paradigm in biological studies, which in turn leads to a new - search paradigm in mathematics, physics, and computer science and moves forward with the interplays among experimental studies and outcomes, simulation studies, and theoretical investigations.