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 hottopics 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.
