Soft Matter / Biological Physics

The book provides a new conceptual scaffold for further research in biology and cognition by introducing the new field of Cognitive Biology. It is a systems biology approach showing that further progress in this field will depend on a deep recognition of developmental processes, as well as on the consideration of the developed organism as an agent able to modify and control its surrounding environment. The role of cognition, the means through which the organism is able to cope with its environment, cannot be underestimated. In particular, it is shown that this activity is grounded on a theory of information based on Bayesian probabilities. The organism is considered as a cybernetic system able to integrate a processor as a source of variety (the genetic system), a regulator of its own homeostasis (the metabolic system), and a selecting system separating the self from the non-self (the membrane in unicellular organisms).

The aim of this book is to understand networks and the basic principles of their structural organization and evolution. The ideas are presented in a clear and a pedagogical way. Special attention is given to real networks, both natural and artificial, including the Internet and the World Wide Web. Collected empirical data and numerous real applications of existing theories are discussed in detail, as well as the topical problems of communication and other networks.

I describe my life from the age of 5 in 1939 through to 2010. The first chapter describes my evacuation to Devon during the blitz and following the V1 and V2 attacks on London. At the end of hostilities I worked briefly in the printing industry but decided to pursue my real interests in science by joining the Rocket Propulsion Department at Westcott near Aylesbury. Following National Service and University I married and went to the USA for 2 years returning in 1964 as a Lecturer in Physics at the University of Nottingham. In 1972 I spent a sabbatical period in Heidleberg. During this period I interacted with my student, Peter Grannell, in Nottingham on the then novel idea of magnetic resonance imaging which led to my first paper on MRI presented at the first Specialised Colloque Ampère held in Krakow in 1973. Later in 1975 I met Godfrey Hounsfield, inventor of the CT scanner, at the EMI Central Research Laboratories in Hayes, Middlesex. This meeting sparked of an interest leading to EMI producing their own MRI scanner. In 1980-82 other MRI groups at Nottingham, led by Professor Andrew and Dr Moore, left Nottingham to set up in the U.S.A. This exodus left me free to steam on with my group’s developments of high speed imaging. These were the Golden Years in MRI at Nottingham. In 1987 a new Vice Chancellor, Colin Campbell took over the running of the University of Nottingham. He was extremely helpful to me in our acquiring a new building dedicated to our work with MRI. In the early 90’s there was considerable speculation about whether there should be a Nobel Prize in MRI. This speculation was initiated in the U.S.A by the Journal “Diagnostic Imaging”. But interest soon faded. Further developments in MRI led finally to a Nobel Prize in Physiology or Medicine in 2003 awarded jointly with Paul Lauterbur. There were some antagonisims to MRI especially from Raymond Damadian, but these were settled or ignored. New ideas for reducing acoustic noise were explored and a 50 dB reduction achieved on a rectangular plate construction. However, on a circular gradient coil system, the best noise reduction achieved was around 30 dB. My two brothers, Conrad and Sidney together with a number of friends and colleagues central to my progress in MRI, are included in the Epilogue.

The human genome of three billion letters has been sequenced. So have the genomes of thousands of other organisms. With unprecedented resolution, modern technologies are allowing us to peek into the world of genes, biomolecules, and cells, and flooding us with data of immense complexity that we are just barely beginning to understand. A huge gap separates our knowledge of the components of a cell and what is known from our observations of its physiology. This book explores what has been done to close this gap of understanding between the realms of molecules and biological processes. It contains illustrative mechanisms and models of gene regulatory networks, DNA replication, the cell cycle, cell death, differentiation, cell senescence, and the abnormal state of cancer cells. The mechanisms are biomolecular in detail, and the models are mathematical in nature.

In July 2009, many experts in the mathematical modelling of biological sciences gathered in Les Houches for a four-week summer school on the mechanics and physics of biological systems. The goal of the school was to present to students and researchers an integrated view of new trends and challenges in physical and mathematical aspects of biomechanics. While the scope for such a topic was very wide, the summer school focused on problems where solid and fluid mechanics play a central role. The school covered both the general mathematical theory of mechanical biology in the context of continuum mechanics but also the specific modelling of particular systems in the biology of the cell, plants, microbes, and in physiology. The chapters in this book contain the lecture notes which are organized (as was the school) around five different main topics all connected by the common theme of continuum modelling for biological systems: bio-fluidics, bio-gels, bio-mechanics, bio-membranes, and morphogenesis. These notes are not meant as a journal review of the topic but rather as a gentle tutorial introduction on the basic problematic in modelling biological systems from a mechanics perspective.

Brownian diffusion is the motion of one or more solute molecules in a sea of very many, much smaller solvent molecules. Its importance today owes mainly to cellular chemistry, since Brownian diffusion is one of the ways in which key reactant molecules move about inside a living cell. This book focuses on the four simplest models of Brownian diffusion: the classical Fickian model, the Einstein model, the discrete-stochastic (cell-jumping) model, and the Langevin model. The book carefully develops the theories underlying these models, assess their relative advantages, and clarify their conditions of applicability. Special attention is given to the stochastic simulation of diffusion, and to showing how simulation can complement theory and experiment. Two self-contained tutorial chapters, one on the mathematics of random variables and the other on the mathematics of continuous Markov processes (stochastic differential equations), make the book accessible to researchers from a broad spectrum of technical backgrounds.