The E M B 0 course on "Formal Analysis of Genetic Regulation" A course entitled "Formal analysis of Genetic Regulation" was held at the University of Brussels from 6 to 16 September 1977 under the auspices of EMBO (European Molecular Biology Organization). As indicated by the title of the book (but not explicitly enough by the title of the course), the main emphasis was put on a dynamic analysis of systems using logical methods, that is, methods in which functions and variables take only a limited number of values - typically two. In this respect, this course was complementary to an EMBO course using continuous methods which was held some months later in Israel by Prof. Segel. People from four very different laboratories took an active part in teaching our course in Brussels : Drs Anne LEUSSLER and Philippe VAN HAM, from the Laboratory of Prof. Jean FLORINE (Laboratoire des Systemes logiques et numeriques, Faculte des Sciences appliquees, Universite Libre de Bruxelles). Dr Stuart KAUFFMAN (Dept. of Biochemistry and Biophysics, School of Medicine, Philadelphia). Prof. Gregoire NICOLlS (Service de Biophysique Theorique, Faculte des Sciences, Universite Libre de Bruxelles) and his temporary coworker Dr David RIGNEY (presently at the Center for Statistical Mechanics and Thermodynamics of the University of Texas at Austin, Texas).

This is a graduate-level introduction to quantitative concepts and methods in the science of living systems. It relies on a systems approach for understanding the physical principles operating in biology. Physical phenomena are treated at the appropriate spatio-temporal scale and phenomenological equations are used in order to reflect the system of interest. Biological details enter to the degree necessary for understanding specific processes, but in many cases the approach is not reductionist. This is in line with the approach taken by physics to many other complex systems. The book bridges the gap between graduate students’ general physics courses and research papers published in professional journals. It gives students the foundations needed for independent research in biological physics and for working in collaborations aimed at quantitative biology and biomedical research. Also included are modern mathematical and theoretical physics methods, giving the student a broad knowledge of tools that can shed light on the sophisticated mechanisms brought forth by evolution in biological systems. The content covers many aspects that have been the focus of active research over the past twenty years, reflecting the authors' experience as leading researchers and teachers in this field.

This edited collection, first published in 1987, provides a comparative analysis of different approaches to urban modelling, and lays the foundations for the possibility of integration and a more unified field. The first part contextualises the development of the field of urban systems modelling, focusing on the variety of approaches and possible implications of this on the future of research and methodology. Next, the editors consider economic and ‘non-economic’ approaches, followed by an analysis of spatial-interaction-based approaches. Providing an overview to the field and research literature, the overarching argument is that there should be an integrated methodological approach to urban system modelling.

Depth Perception in Frogs and Toads provides a comprehensive exploration of the phenomenon of depth perception in frogs and toads, as seen from a neuro-computational point of view. Perhaps the most important feature of the book is the development and presentation of two neurally realizable depth perception algorithms that utilize both monocular and binocular depth cues in a cooperative fashion. One of these algorithms is specialized for computation of depth maps for navigation, and the other for the selection and localization of a single prey for prey catching. The book is also unique in that it thoroughly reviews the known neuroanatomical, neurophysiological and behavioral data, and then synthesizes, organizes and interprets that information to explain a complex sensory-motor task. The book will be of special interest to that segment of the neural computing community interested in understanding natural neurocomputational structures, particularly to those working in perception and sensory-motor coordination. It will also be of interest to neuroscientists interested in exploring the complex interactions between the neural substrates that underly perception and behavior.

Now in its second edition, this handbook collects authoritative contributions on modern methods and tools in statistical bioinformatics with a focus on the interface between computational statistics and cutting-edge developments in computational biology. The three parts of the book cover statistical methods for single-cell analysis, network analysis, and systems biology, with contributions by leading experts addressing key topics in probabilistic and statistical modeling and the analysis of massive data sets generated by modern biotechnology. This handbook will serve as a useful reference source for students, researchers and practitioners in statistics, computer science and biological and biomedical research, who are interested in the latest developments in computational statistics as applied to computational biology.

This book develops a new naturalist theory of reason and scientific knowledge from a synthesis of philosophy and the new sciences of complex adaptive systems. In particular, the theory of partially self-organizing regulatory systems is now emerging as central to all the life and social sciences, and this book shows how these ideas can be used to illuminate and satisfyingly reconstruct our basic philosophical concepts and principles. Evolutionary epistemology provides a unifying subject for the book. It is taken as proposing some important commonality between cognitive biological and cognitive epistemic processes. Here, that commonality is found by embedding both in a common model of complex adaptive system dynamics. New reconstructions are offered on the theories of Jean Piaget, Karl Popper, and Nicholas Rescher which show how their ideas are more deeply illuminated from this perspective in contrast to the formal rationalist interpretations standard among philosophers and scientists.

The diversity of antigen-binding structures of antibody molecules is so vast that every conceivable antigen can be bound by an antibody molecule within the immune system. This is true even for the antigen binding sites of antibodies called idiotypes, which are bound by complementary bind ing sites of other antibodies called anti-idiotypes. Thus, anti-idiotypes are structural homologues of antigens. These idiotypic-anti-idiotypic interactions constitute a network within the immune system. Since one lymphocyte produces only one type of antibody molecule, this network is in fact a network of cells. We expect that the network is functional: the appearance of antigen will disturb the equilibrium of the network at the point where it competes with the anti idiotypic lymphocyte for binding to the idiotypic lympho cyte. It has been known for quite some time that anti idiotypic antibody can be used to prime the immune system for memory to an antigen that it has never seen. This phe nomenon is now being explored for possible use in immuni zation against viruses, bacteria, parasites and tumors as well as for the modulation of autoimmunity. The ability of anti-idiotypes to mimic, both antigenically and function ally, the corresponding biologically active molecules seen by an idiotypic antibody was first demonstrated for the hormone insulin and is now being observed in many other systems. The papers assembled in this volume· bring the reader to the cutting edge of the potential practical applica tions of the network theory of the immune system.

This volume contains the refereed and revised papers of the Fourth International Conference on Design Computing and Cognition (DCC'10), held in Stuttgart, Germany. The material in this book represents the state-of-the-art research and developments in design computing and design cognition. The papers are grouped under the following nine headings, describing both advances in theory and application and demonstrating the depth and breadth of design computing and design cognition: Design Cognition; Framework Models in Design; Design Creativity; Lines, Planes, Shape and Space in Design; Decision-Making Processes in Design; Knowledge and Learning in Design; Using Design Cognition; Collaborative/Collective Design; and Design Generation. This book is of particular interest to researchers, developers and users of advanced computation in design across all disciplines and to those who need to gain better understanding of designing.

The NATO workshop on Disordered Systems and Biological Organization was attended, in march 1985, by 65 scientists representing a large variety of fields: Mathematics, Computer Science, Physics and Biology. It was the purpose of this interdisciplinary workshop to shed light on the conceptual connections existing between fields of research apparently as different as: automata theory, combinatorial optimization, spin glasses and modeling of biological systems, all of them concerned with the global organization of complex systems, locally interconnected. Common to many contributions to this volume is the underlying analogy between biological systems and spin glasses: they share the same properties of stability and diversity. This is the case for instance of primary sequences of biopo Iymers I ike proteins and nucleic acids considered as the result of mutation-selection processes [P. W. Anderson, 1983] or of evolving biological species [G. Weisbuch, 1984]. Some of the most striking aspects of our cognitive apparatus, involved In learning and recognttlon [J. Hopfield, 19821, can also be described in terms of stability and diversity in a suitable configuration space. These interpretations and preoccupations merge with those of theoretical biologists like S. Kauffman [1969] (genetic networks) and of mathematicians of automata theory: the dynamics of networks of automata can be interpreted in terms of organization of a system in multiple possible attractors. The present introduction outlInes the relationships between the contributions presented at the workshop and brIefly discusses each paper in its particular scientific context.