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(More customer reviews)Regulatory networks are central to every aspect of computational biology. Determining what they are, and what genes, proteins, and post-translational modifications interact is a major and exciting field of study.
I just didn't come away from this book with that excitement. I was hoping for more about the large-scale regulation networks, but these papers go down to the quantum mechanics of interactions between pairs of molecules. I appreciate that the exact interactions matter, and that computation is probably the only way to examine some kinds of interactions (e.g. the ones in lethal mutations). It's just not what I think of as a "network."
I was also hoping for some more specifics about the computation techniques. There were some interesting insights here. For example, I never thought about the similarities between steady state chemical equilibrium and steady state Markov model behavior before, but the formalisms have striking similarities. I was also interested in some of the information-based measures for determining how well a model represents a system. I learned that the statistical assumptions behind normal chemical "equilibrium" break down at the scale of bacteria - instead, presence or absence of individual molecules matters more. Still, those were isolated kinds of facts and never came together into a whole for me.
The range of views was worthwhile. On the whole, though, the models all seemed very low-level to me, probably not well suited to handling more than a few dozen interactions, and the computation specifics were not always explicit. I'm still looking for a book with more information that I can apply directly.
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Computational Modeling of Genetic and Biochemical Networks (Computational Molecular Biology)The advent of ever more sophisticated molecular manipulation techniqueshas made it clear that cellular systems are far more complex and dynamic thanpreviously thought. At the same time, experimental techniques are providing analmost overwhelming amount of new data. It is increasingly apparent that linkingmolecular and cellular structure to function will require the use of newcomputational tools.This book provides specific examples, across a wide range ofmolecular and cellular systems, of how modeling techniques can be used to explorefunctionally relevant molecular and cellular relationships. The modeling techniquescovered are applicable to cell, developmental, structural, and mathematical biology;genetics; and computational neuroscience. The book, intended as a primer for boththeoretical and experimental biologists, is organized in two parts: models of geneactivity and models of interactions among gene products. Modeling examples areprovided at several scales for each subject. Each chapter includes an overview ofthe biological system in question and extensive references to important work in thearea.
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