Mathematical Hierarchies And Biology

Twenty-four articles from the November 1996 workshop investigate the reconstruction of trees or ranking hierarchies from dissimilarity or entity-to-character data, the use of hierarchies for modeling evolution and other processes, and the combining of gene trees. Included are mathematical treatments of hierarchies in the frameworks of set systems, linear subspaces, graph objects, and tree metrics in their analyses. Such current applications as learning robots, intron evolution, and the development of language are addressed. Annotation copyrighted by Book News, Inc., Portland, OR.

Twenty-four articles from the November 1996 workshop investigate the reconstruction of trees or ranking hierarchies from dissimilarity or entity-to-character data, the use of hierarchies for modeling evolution and other processes, and the combining of gene trees. Included are mathematical treatments of hierarchies in the frameworks of set systems, linear subspaces, graph objects, and tree metrics in their analyses. Such current applications as learning robots, intron evolution, and the development of language are addressed. Annotation copyrighted by Book News, Inc., Portland, OR.

The mathematical approach to the study of hierarchies presents the theoretical basis for many important areas of current scientific investigation. Biology has benefited from this research and has also stimulated the mathematical study of hierarchies. This collection presents papers devoted to theoretical, algorithmical, and application issues related to (1) reconstructing hierarchies (trees or ranking) from (dis)similarity or entity-to-character data, (2) using hierarchies for modeling evolution and other processes, and (3) combining (gene) trees. The papers in this volume provide a contempora.

Foundations of Mathematical Biology, Volume 1, Subcellular Systems, provides an introduction the place of mathematical biology in relation to the other biological, physical, and organizational sciences. It discusses the use of mathematical tools and techniques to solve biological problems. The book contains four chapters and begins with a discussion of the nature of hierarchical control in living matter. This is followed by a chapter on chemical kinetics and enzyme kinetics, covering the physicomathematical principles, models, and approximations underlying transition-state theory and the unimolecular reaction. Subsequent chapters deal with quantum genetics and membrane excitability.

The topic of the book a theory of functional biology thatincorporates the fundamental principles underlying the functioning ofliving organisms is clearly appropriate as we celebrate the 50thanniversary of the discovery by Watson and Crick of the structure ofthe DNA molecule.

Memory Evolutive Systems; Hierarchy, Emergence, Cognition provides comprehensive and comprehensible coverage of Memory Evolutive Systems (MEM). Written by the developers of the MEM, the book proposes a mathematical model for autonomous evolutionary systems based on the Category Theory of mathematics. It describes a framework to study and possibly simulate the structure of living systems and their dynamic behavior. This book contributes to understanding the multidisciplinary interfaces between mathematics, cognition, consciousness, biology and the study of complexity. It is organized into three parts. Part A deals with hierarchy and emergence and covers such topics as net of interactions and categories; the binding problem; and complexifications and emergence. Part B is about MEM while Part C discusses MEM applications to cognition and consciousness. The book explores the characteristics of a complex evolutionary system, its differences from inanimate physical systems, and its functioning and evolution in time, from its birth to its death. This book is an ideal reference for researchers, teachers and students in pure mathematics, computer science, cognitive science, study of complexity and systems theory, Category Theory, biological systems theory, and consciousness theory. It would also be of interest to both individuals and institutional libraries. Comprehensive and comprehensible coverage of Memory Evolutive System Written by the developers of the Memory Evolutive Systems Designed to explore the common language between sciences

This book is devoted to a novel conceptual theoretical framework of neuro science and is an attempt to show that we can postulate a very small number of assumptions and utilize their heuristics to explain a very large spectrum of brain phenomena. The major assumption made in this book is that inborn and acquired neural automatisms are generated according to the same func tional principles. Accordingly, the principles that have been revealed experi mentally to govern inborn motor automatisms, such as locomotion and scratching, are used to elucidate the nature of acquired or learned automat isms. This approach allowed me to apply the language of control theory to describe functions of biological neural networks. You, the reader, can judge the logic of the conclusions regarding brain phenomena that the book derives from these assumptions. If you find the argument flawless, one can call it common sense and consider that to be the best praise for a chain of logical conclusions. For the sake of clarity, I have attempted to make this monograph as readable as possible. Special attention has been given to describing some of the concepts of optimal control theory in such a way that it will be under standable to a biologist or physician. I have also included plenty of illustra tive examples and references designed to demonstrate the appropriateness and applicability of these conceptual theoretical notions for the neurosciences.

THE MATHEMATICAL BIOLOGY OF DIATOMS This book contains unique, advanced applications using mathematics, algorithmic techniques, geometric analysis, and other computational methods in diatom research. Historically, diatom research has centered on taxonomy and systematics. While these topics are of the utmost importance, other aspects of this important group of unicells have been increasingly explored in the biological sciences. While mathematical applications are still rare, they are starting take hold and provide an extensive avenue of new diatom research, including applications in multidisciplinary fields. The work contained in this volume is an eclectic mix of analytical studies on diatoms. Mathematical treatment of the various biological disciplines covered in this book range from implicit, but succinct studies to more elaborate detailed computational studies. Topics include growth models, nanostructure, nanoengineering, cell growth, araphid diatoms, valve ontogeny, diatom metabolism, diatom motility, synchronization, diatom kinematics, photonics, biogenic sensors, photochemistry, diatom light response, colony growth, siliceous unicells, algal kinetics, diatom structure, diatom imaging, functional morphology, geometric structure, biomineralization, high-resolution imaging, non-destructive imaging, and 3D structure. This wide-ranging volume provides an introductory as well as an advanced treatment of recent interests in diatom research. The mathematical research in this volume may be applicable to studies of other unicells, biomechanics, biological processes, physio-chemical analyses, or nanoscience.