This book describes the evolution of several socio-biological systems using mathematical kinetic theory. Specifically, it deals with modeling and simulations of biological systems whose dynamics follow the rules of mechanics as well as rules governed by their own ability to organize movement and biological functions. It proposes a new biological model focused on the analysis of competition between cells of an aggressive host and cells of a corresponding immune system. Proposed models are related to the generalized Boltzmann equation. The book may be used for advanced graduate courses and seminars in biological systems modeling.

Mathematical Models of Life Support Systems is a component of Encyclopedia of Mathematical Sciences in which is part of the global Encyclopedia of Life Support Systems (EOLSS), an integrated compendium of twenty one Encyclopedias. The Theme is organized into several topics which represent the main scientific areas of the theme: The first topic, Introduction to Mathematical Modeling discusses the foundations of mathematical modeling and computational experiments, which are formed to support new methodologies of scientific research. The succeeding topics are Mathematical Models in - Water Sciences; Climate; Environmental Pollution and Degradation; Energy Sciences; Food and Agricultural Sciences; Population; Immunology; Medical Sciences; and Control of Catastrophic Processes. These two volumes are aimed at the following five major target audiences: University and College students Educators, Professional practitioners, Research personnel and Policy analysts, managers, and decision makers and NGOs.

This monograph has the ambitious aim of developing a mathematical theory of complex biological systems with special attention to the phenomena of ageing, degeneration and repair of biological tissues under individual self-repair actions that may have good potential in medical therapy.The approach to mathematically modeling biological systems needs to tackle the additional difficulties generated by the peculiarities of living matter. These include the lack of invariance principles, abilities to express strategies for individual fitness, heterogeneous behaviors, competition up to proliferative and/or destructive actions, mutations, learning ability, evolution and many others. Applied mathematicians in the field of living systems, especially biological systems, will appreciate the special class of integro-differential equations offered here for modeling at the molecular, cellular and tissue scales. A unique perspective is also presented with a number of case studies in biological modeling.

This monograph has the ambitious aim of developing a mathematical theory of complex biological systems with special attention to the phenomena of ageing, degeneration and repair of biological tissues under individual self-repair actions that may have good potential in medical therapy.The approach to mathematically modeling biological systems needs to tackle the additional difficulties generated by the peculiarities of living matter. These include the lack of invariance principles, abilities to express strategies for individual fitness, heterogeneous behaviors, competition up to proliferative and/or destructive actions, mutations, learning ability, evolution and many others.Applied mathematicians in the field of living systems, especially biological systems, will appreciate the special class of integro-differential equations offered here for modeling at the molecular, cellular and tissue scales. A unique perspective is also presented with a number of case studies in biological modeling.

Mathematical Models of Life Support Systems is a component of Encyclopedia of Mathematical Sciences in which is part of the global Encyclopedia of Life Support Systems (EOLSS), an integrated compendium of twenty one Encyclopedias. The Theme is organized into several topics which represent the main scientific areas of the theme: The first topic, Introduction to Mathematical Modeling discusses the foundations of mathematical modeling and computational experiments, which are formed to support new methodologies of scientific research. The succeeding topics are Mathematical Models in - Water Sciences; Climate; Environmental Pollution and Degradation; Energy Sciences; Food and Agricultural Sciences; Population; Immunology; Medical Sciences; and Control of Catastrophic Processes. These two volumes are aimed at the following five major target audiences: University and College students Educators, Professional practitioners, Research personnel and Policy analysts, managers, and decision makers and NGOs.

This is a book of an international series on interdisciplinary topics of the Mathematical and Biological Sciences. The chapters are related to selected papers on the research themes presented at BIOMAT 2015 International Symposium on Mathematical and Computational Biology which was held in the Roorkee Institute of Technology, in Roorkee, Uttarakhand, India, on November 02-06, 2015. The treatment is both pedagogical and advanced in order to motivate research students to fulfill the requirements of professional practitioners. As in other volumes of this series, there are new important results on the interdisciplinary fields of mathematical and biological sciences and comprehensive reviews written by prominent scientific leaders of famous research groups.There are new results based on the state of art research in Population Dynamics, on Pattern Recognition of Biological Phenomena, the Mathematical Modelling of Infectious Diseases, Computational Biology, the Dynamic and Geometric Modelling of Biological Phenomena, the Modelling of Physiological Disorders, the Optimal Control Techniques in Mathematical Modelling of Biological Phenomena, the Hydrodynamics and Elasticity of Cell Tissues and Bacterial Growth and the Mathematical Morphology of Biological Structures. All these contributions are also strongly recommended to professionals from other scientific areas aiming to work on these interdisciplinary fields.

Written and edited by some of the most well-respected authors in the area of the adaptation of plants and animals to climate change, this groundbreaking new work is an extremely important scientific contribution to the study of global warming. Global climate change is one of the most serious and pressing issues facing our planet. Rather than a "silver bullet" or a single study that solves it, the study of global climate change is like a beach, with each contribution a grain of sand, gathered together as a whole to create a big picture, moving the science forward. This new groundbreaking study focuses on the adaptation and tolerance of plants and animal life to the harsh conditions brought on by climate change or global warming. Using the papers collected here, scientists can better understand global climate change, its causes, results, and, ultimately, the future of life on our planet. The first section lays out a methodology and conceptual direction of the work as a whole, covering the modeling, approaches, and the impacts studied throughout the book. The second section focuses on certain hypotheses laid out by the authors regarding how plants and animal life can adapt and survive in extreme environments. The third section compiles a series of ecological experiments and their conclusions, and a final section is dedicated to previous scientific breakthroughs in this field and the scientists who made them. Whether for the scientist in the field, the student, or as a reference, this groundbreaking new work is a must-have. Focusing on a small part of the global climate change "beach," this "grain of sand" is an extremely important contribution to the scientific literature and a step forward in understanding the problems and potentialities of the issue.

This work aims to foster the interdisciplinary dialogue between mathematicians and socio-economic scientists. Interaction among scholars and practitioners traditionally coming from different research areas is necessary more than ever in order to better understand many real-world problems we face today. On the one hand, mathematicians need economists and social scientists to better address the methodologies they design in a more realistic way; on the other hand, economists and social scientists need to be aware of sound mathematical modelling tools in order to understand and, ultimately, solve the complex problems they encounter in their research. With this goal in mind, this work is designed to take into account a multidisciplinary approach that will encourage the transfer of knowledge, ideas, and methodology from one discipline to the other. In particular, the work has three main themes: Demystifying and unravelling complex systems; Introducing models of individual behaviours in the social and economic sciences; Modelling socio-economic sciences as complex living systems. Specific tools examined in the work include a recently developed modelling approach using stochastic game theory within the framework of statistical mechanics and progressing up to modeling Darwinian evolution. Special attention is also devoted to social network theory as a fundamental instrument for the understanding of socio-economic systems.​

Volume I of this two-volume, interdisciplinary work is a unified presentation of a broad range of state-of-the-art topics in the rapidly growing field of mathematical modeling in the biological sciences. The chapters are thematically organized into the following main areas: cellular biophysics, regulatory networks, developmental biology, biomedical applications, data analysis and model validation. The work will be an excellent reference text for a broad audience of researchers, practitioners, and advanced students in this rapidly growing field at the intersection of applied mathematics, experimental biology and medicine, computational biology, biochemistry, computer science, and physics.

:Computer modeling of biological systems, a process of building new sets of conceptualizations, theories, and implementations is cov-ered in depth. The emphasis is on how computer modeling encom-passes three distinct areas of science (computer science, biology, and medicine) for building a framework for investigating the behavior of a complex biological system. Simulation and modeling are dis-cussed because these two factors provide the methodology for the design, development, experimentation, analysis, and evaluation of a experiment under study. Because of their high degree of modular-ity and collective complexity, computer systems such as analog, digital, or hybrid are reviewed. This presentation of computer mod-eling of biological systems delves into the study of data represen-tation (or data structures) and their transformation into an empirical model via a software program.