Mathematical Models and Methods for Living Systems: Levico Terme, Italy 2014

Springer Proceedings in Mathematics & Statistics

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This Volume comprises of 13 chapters, including an overview chapter, providing an up-to-date and state-of-the research on the application of intelligent optimization for bioinformatics applications, DNA based Steganography, a modified Particle Swarm Optimization Algorithm for Solving Capacitated Maximal Covering Location Problem in Healthcare Systems, Optimization Methods for Medical Image Super Resolution Reconstruction and breast cancer classification.

The book will be a useful compendium for a broad range of readers- from students of undergraduate to postgraduate levels and also for researchers, professionals, etc. A biological model for controlling interface growth and morphology. Summary Biological systems create proteins that perform tasks more efficiently and precisely than conventional chemicals. For example, many plants and animals produce proteins to control the freezing of water.

Biological antifreeze proteins AFPs inhibit the solidification process, even below the freezing point.

Levico Terme, Italy 2014

In this project, we investigated the theoretical and experimental data on AFPs and performed analyses to understand the unique physics of AFPs. Stearic pinning was found to be the most likely candidate to explain experimental results, including freezing point depression, growth morphologies, and thermal hysteresis. A new stearic pinning model was developed and applied to AFPs, with excellent quantitative results.

Understanding biological antifreeze mechanisms could enable important medical and engineering applications, but considerable future work will be necessary. Modeling life : the mathematics of biological systems [].

Mathematical models and methods for living systems : Levico terme, Italy 2014

Garfinkel, Alan, author. Cham, Switzerland : Springer, Description Book — xv, pages : illustrations some color ; 27 cm Summary 1. Modeling, Change, and Simulation. Derivatives and Integrals. Equilibrium Behavior. Non-Equilibrium Dynamics: Oscillation. Linear Algebra. Multivariable Systems. From predator-prey populations in an ecosystem, to hormone regulation within the body, the natural world abounds in dynamical systems that affect us profoundly. Complex feedback relations and counter-intuitive responses are common in nature; this book develops the quantitative skills needed to explore these interactions.

Differential equations are the natural mathematical tool for quantifying change, and are the driving force throughout this book. The use of Euler's method makes nonlinear examples tractable and accessible to a broad spectrum of early-stage undergraduates, thus providing a practical alternative to the procedural approach of a traditional Calculus curriculum.

Tools are developed within numerous, relevant examples, with an emphasis on the construction, evaluation, and interpretation of mathematical models throughout. Encountering these concepts in context, students learn not only quantitative techniques, but how to bridge between biological and mathematical ways of thinking.

Examples range broadly, exploring the dynamics of neurons and the immune system, through to population dynamics and the Google PageRank algorithm. Each scenario relies only on an interest in the natural world; no biological expertise is assumed of student or instructor. Building on a single prerequisite of Precalculus, the book suits a two-quarter sequence for first or second year undergraduates, and meets the mathematical requirements of medical school entry.

The later material provides opportunities for more advanced students in both mathematics and life sciences to revisit theoretical knowledge in a rich, real-world framework. In all cases, the focus is clear: how does the math help us understand the science? G Unknown. Mathematical models and methods for living systems : Levico Terme, Italy []. Description Book — xi, pages : illustrations some color ; 24 cm. Preziosi and M. The aim of these lecture notes is to give an introduction to several mathematical models and methods that can be used to describe the behaviour of living systems.

This emerging field of application intrinsically requires the handling of phenomena occurring at different spatial scales and hence the use of multiscale methods. Modelling and simulating the mechanisms that cells use to move, self-organise and develop in tissues is not only fundamental to an understanding of embryonic development, but is also relevant in tissue engineering and in other environmental and industrial processes involving the growth and homeostasis of biological systems.

Growth and organization processes are also important in many tissue degeneration and regeneration processes, such as tumour growth, tissue vascularization, heart and muscle functionality, and cardio-vascular diseases. Algebraic and discrete mathematical methods for modern biology []. London, UK : Academic Press, Description Book — 1 online resource Summary Written by experts in both mathematics and biology, Algebraic and Discrete Mathematical Methods for Modern Biology offers a bridge between math and biology, providing a framework for simulating, analyzing, predicting, and modulating the behavior of complex biological systems.

Each chapter begins with a question from modern biology, followed by the description of certain mathematical methods and theory appropriate in the search of answers. Every topic provides a fast-track pathway through the problem by presenting the biological foundation, covering the relevant mathematical theory, and highlighting connections between them. Many of the projects and exercises embedded in each chapter utilize specialized software, providing students with much-needed familiarity and experience with computing applications, critical components of the "modern biology" skill set.

Content Types

Mathematical models in developmental biology []. Percus, Jerome K. Jerome Kenneth , author. Summary Introduction Catastrophe theory Pattern formation Differential adhesion and morphogenesis The origins of movement Chemotaxis Cell proliferation Somite formation in vertebrates Compartments Segmentation of insect embryos Supplementary notes Bibliography Index.

Its complexity calls for a very high level of organization, with an array of subprocesses in constant communication with each other.

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These notes introduce an interleaved set of mathematical models representative of research in the last few decades, as well as the techniques that have been developed for their solution. Such models offer an effective way of incorporating reliable data in a concise form, provide an approach complementary to the techniques of molecular biology, and help to inform and direct future research.

P36 Unknown. Methods and models in mathematical biology : deterministic and stochastic approaches []. Heidelberg ; New York : Springer, c Description Book — xiii, p.

Summary 1. Compartmental Modelling.

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Mathematical Ecology. Structured Models in Ecology. Reaction Kinetics.

Neuronal Activity. The main themes are modeling principles, mathematical principles for the analysis of these models and model-based analysis of data. The key topics of modern biomathematics are covered: ecology, epidemiology, biochemistry, regulatory networks, neuronal networks and population genetics. A variety of mathematical methods are introduced, ranging from ordinary and partial differential equations to stochastic graph theory and branching processes. A special emphasis is placed on the interplay between stochastic and deterministic models.

M83 Unknown. Shahin, Mazen, author. With an integrated and interdisciplinary approach that embeds mathematical modeling into biological applications, the book illustrates numerous applications of mathematical techniques within biology, ecology, and environmental sciences. The book is also an excellent reference for biologists, ecologists, mathematicians, biomathematicians, and environmental and resource economists. S Unknown. An introduction to mathematical population dynamics : along the trail of Volterra and Lotka [].

Iannelli, Mimmo, author. Cham : Springer, [] Description Book — 1 online resource xiv, pages : illustrations. Summary 1 Malthus, Verhulst and all that. The work is focused on population dynamics and ecology, following a tradition that goes back to Lotka and Volterra, and includes a part devoted to the spread of infectious diseases, a field where mathematical modeling is extremely popular. These themes are used as the area where to understand different types of mathematical modeling and the possible meaning of qualitative agreement of modeling with data.

The book also includes a collections of problems designed to approach more advanced questions. This material has been used in the courses at the University of Trento, directed at students in their fourth year of studies in Mathematics. It can also be used as a reference as it provides up-to-date developments in several areas.

Mathematics for the life sciences []. Bodine, Erin N. Princeton, New Jersey : Princeton University Press, [] Description Book — xx, pages : illustrations some color ; 27 cm Summary The life sciences deal with a vast array of problems at different spatial, temporal, and organizational scales. The mathematics necessary to describe, model, and analyze these problems is similarly diverse, incorporating quantitative techniques that are rarely taught in standard undergraduate courses.

This textbook provides an accessible introduction to these critical mathematical concepts, linking them to biological observation and theory while also presenting the computational tools needed to address problems not readily investigated using mathematics alone. Proven in the classroom and requiring only a background in high school math, Mathematics for the Life Sciences doesn't just focus on calculus as do most other textbooks on the subject.

It covers deterministic methods and those that incorporate uncertainty, problems in discrete and continuous time, probability, graphing and data analysis, matrix modeling, difference equations, differential equations, and much more. The book uses MATLAB throughout, explaining how to use it, write code, and connect models to data in examples chosen from across the life sciences. Provides undergraduate life science students with a succinct overview of major mathematical concepts that are essential for modern biology Covers all the major quantitative concepts that national reports have identified as the ideal components of an entry-level course for life science students Provides good background for the MCAT, which now includes data-based and statistical reasoning Explicitly links data and math modeling Includes end-of-chapter homework problems, end-of-unit student projects, and select answers to homework problems Uses MATLAB throughout, and MATLAB m-files with an R supplement are available online Prepares students to read with comprehension the growing quantitative literature across the life sciences Forthcoming online answer key, solution guide, and illustration package available to professors.

B63 Unknown. Stochastic dynamics for systems biology []. Mazza, Christian. Description Book — xii, p. The book shows how the mathematical models are used as technical tools for simulating biological processes and how the models lead to conceptual insights on the functioning of the cellular processing system. Most of the text should be accessible to scientists with basic knowledge in calculus and probability theory.

The authors illustrate the relevant Markov chain theory using realistic models from systems biology, including signaling and metabolic pathways, phosphorylation processes, genetic switches, and transcription. A central part of the book presents an original and up-to-date treatment of cooperativity. The book defines classical indexes, such as the Hill coefficient, using notions from statistical mechanics. It explains why binding curves often have S-shapes and why cooperative behaviors can lead to ultrasensitive genetic switches.

These notions are then used to model transcription rates. Examples cover the phage lambda genetic switch and eukaryotic gene expression.

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