Statistical Mechanics of Biocomplexity: Proceedings of the XV Sitges Conference Held at Sitges, Barcelona, Spain, 8–12 June 1998

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Edition: 1

Series: Lecture Notes in Physics 527

ISBN: 3540662456, 9783540662457

Size: 2 MB (2527614 bytes)

Pages: 320/327

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Reinhard Lipowsky (auth.), D. Reguera, J.M.G. Vilar, J.M. Rubí (eds.)3540662456, 9783540662457

This book demonstrates the usefulness of tools from statistical mechanics for biology. It includes the new tendencies in topics like membranes, vesicles, microtubules, molecular motors, DNA, protein folding, phase transitions in biological systems, evolution, population dynamics, neural systems and biological oscillators, with special emphasis on the importance of statistical mechanics in their development. The book addresses researchers and graduate students.

Table of contents :
From membranes to membrane machines….Pages 1-23
‘Sausage string’ patterns in blood vessels at high blood pressures….Pages 24-37
Phase transitions in mesoscopic spherical membranes….Pages 38-45
Modeling microtubule oscillations [1] ….Pages 46-55
Designing RNA folding cooperativity….Pages 56-61
Scaling laws for protein folding….Pages 62-71
Self-organizing networks of molecular machines in allosterically regulated enzymic reactions….Pages 72-92
Coupled Brownian motors….Pages 93-111
On the role of molecular machines in the origin of the genetic code….Pages 112-123
Population dynamics and non-Hermitian localization….Pages 124-151
Collective motion….Pages 152-164
A population dynamics approach to biological aging….Pages 165-171
Small-world networks….Pages 172-172
Extended mean-field theory for networks of spiking neurons….Pages 173-173
Pattern formation in the developing visual cortex: Topological defects, their generation, motion, and annihilation….Pages 174-193
Complex spiking behavior from noise-driven neuron interaction….Pages 194-204
A new nonlinear model for pitch perception….Pages 205-216
Statistical mechanics of network models of macroevolution and extinction….Pages 217-250
Exact analytical results in a simple model of self-organized biological evolution….Pages 251-260
Transition to chaos in models of genetic networks….Pages 261-274

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