Fractals in Molecular Biophysics (Topics in Physical Chemistry)
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Fractals in Molecular Biophysics (Topics in Physical Chemistry)

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Fractals in Molecular Biophysics (Topics in Physical Chemistry)

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T**.

Fractals Less Novel, Cell Switches Less So...

In other words, the "heydey" of chaos, strange attractors and fractals being applied to everything when this book was written has hit one peak, but many of the concepts in this fine volume are nowhere near antique, and new peaks, though more disperse, are still happening.Some of the author's ideas are not only timeless, but deserve a new volume/edition or three:-- In coding/replication linearity (eg. genetics) (small inputs = small outputs) are welcome to avoid mistakes and maintain homeostasis, as in comparing strands for duplication. In adjusting to unexpected environmental change, nonlinear controls (chaotic but controlled around a strange attractor) give the option of small inputs with big outputs-- greater or more dramatic control in responding with or to, say, mutations or climate change.-- Oscillation is all about feedback, the heart of cellular switching, hardly a dusty topic today. The "dynamical systems" (not just time or power series, but ODE's representing bigger cycles than or with oscillation) that also flourished in the early 2000's, still have many novel and cutting edge applications in more complex areas of protein relaxation, percolation (ok, more biophysics than bichem, but hey, that's the book's title!), kinetics, diffusion, and one of the (still) biggest topics in biochemistry, polymers. The authors well anticipated today's research in many of those areas. Homeodynamics hasn't really taken over Homeostasis as they predict, but certainly has made inroads!-- Statistical mechanics, not covered as extensively as in McQuarrie (Statistical Mechanics), still has many complexity theory aspects being explored today, even though the topic also was in its heyday from the 60's through the late 80's (before about 1970 more often called statistical thermodynamics). The authors wryly point out the once you've broken down problems with as much reductionism as possible, you start running into nonlinear issues that can't be linearized and have to be handled with complex and chaotic dynamics. Or, considered stochastic when we think they're really determined, but are not sure how. Not perfect, but handy. Or as Box would say, wrong, but useful.Also a great foundation, even though dated, for understanding more recent journal articles on slices of the many topics covered. It is not really that complex dynamics have been abandoned, it is that they have become fractal, if not self similar, with different terms like invariance in gauge theories, etc., and thus covered in many more fragmented texts today rather than looking at great breadth with less depth.IOW it would be tough to do this volume again today, not because it is irrelevant, but because, after pulling the fragments together, it would be 20 volumes! Highly recommended for a specialized view of a specialized aspect of Biophysics and Biochem, and for fertile research areas, such as relating thermodynamic functions to quantum equations in p-chem, which is where "Probabalistic mechanics" often resides today. Eg-- random/encoded walks are given a great intro here (p. 187).Library Picks reviews only for the benefit of Amazon shoppers and has nothing to do with Amazon, the authors, manufacturers or publishers of the items we review. We always buy the items we review for the sake of objectivity, and although we search for gems, are not shy about trashing an item if it's a waste of time or money for Amazon shoppers. If the reviewer identifies herself, her job or her field, it is only as a point of reference to help you gauge the background and any biases.

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