Diabetes Systems Biology provides senior undergraduate students and junior scientists, interested in diabetes systems biology, with a tool to learn more about the mathematical models and methods used to understand macroscopically and microscopically beta-cell behaviour in health and disease. The book introduces readers to the quantitative methods used to examine beta-cell dynamics, islet biology and architecture, as well as diabetes etiology and implications. The goal is to allow junior researchers in the fields of mathematical biology and biophysics to obtain a broad understanding of these quantitative methods, and guide them into taking the first steps into the field of diabetes systems biology. At the end of each chapter, several problem-solving exercises (that require both analytical and computational skills) are provided for the readers to help them become more proficient in this field. Key Features Comprehensive overview of all relevant aspects of diabetes systems biology and biological mathematical modelling Covers quantitative aspects of this discipline with embedded examples Features contributions from world-class researchers in the field Provides extensive references for further reading Includes problem solving exercises at the end of each chapter

BetaSys uses the example of regulated exocytosis in pancreatic β-cells, and its relevance to diabetes, to illustrate the major concepts of systems biology, its methods and applications.

"This book highlights the use of systems approaches including genomic, cellular, proteomic, metabolomic, bioinformatics, molecular, and biochemical, to address fundamental questions in complex diseases like cancer diabetes but also in ageing"--Provided by publisher.

Genome sequences are now available that enable us to determine the biological components that make up a cell or an organism. The discipline of systems biology examines how these components interact and form networks, and how the networks generate whole cell functions corresponding to observable phenotypes. This textbook, devoted to systems biology, describes how to model networks, how to determine their properties, and how to relate these to phenotypic functions. The prerequisites are some knowledge of linear algebra and biochemistry. Though the links between the mathematical ideas and biological processes are made clear, the book reflects the irreversible trend of increasing mathematical content in biology education. Therefore to assist both teacher and student, in an associated website Palsson provides problem sets, projects and Powerpoint slides, and keeps the presentation in the book concrete with illustrative material and experimental results.

Molecular Nutrition and Diabetes: A Volume in the Molecular Nutrition Series focuses on diabetes as a nutritional problem and its important metabolic consequences. Fuel metabolism and dietary supply all influence the outcome of diabetes, but understanding the pathogenesis of the diabetic process is a prelude to better nutritional control. Part One of the book provides general coverage of nutrition and diabetes in terms of dietary patterns, insulin resistance, and the glucose-insulin axis, while Part Two presents the molecular biology of diabetes and focuses on areas such as oxidative stress, mitochondrial function, insulin resistance, high-fat diets, nutriceuticals, and lipid accumulation. Final sections explore the genetic machinery behind diabetes and diabetic metabolism, including signaling pathways, gene expression, genome-wide association studies, and specific gene expression. While the main focus of each chapter is the basic and clinical research on diabetes as a nutritional problem, all chapters also end with a translational section on the implications for the nutritional control of diabetes. - Offers updated information and a perspective on important future developments to different professionals involved in the basic and clinical research on all major nutritional aspects of diabetes mellitus - Explores how nutritional factors are involved in the pathogenesis of both type1 and type2 diabetes and their complications - Investigates the molecular and genetic bases of diabetes and diabetic metabolism through the lens of a rapidly evolving field of molecular nutrition

The field of diabetes mellitus research is currently characterized by rapid and remarkable growth that has led to the development of significant diagnostic and therapeutic advances. This is very important given the fact that the frequency of the disease continues to increase at alarming rates worldwide. This new volume is a comprehensive overview of the contemporary state of the art in the field. Experts shed light on a broad range of relevant aspects, from genetic background to topics related to diabetic complications such as diabetic retinopathy or diabetic nephropathy. This is expanded upon through papers reporting on the present state of diabetes in pregnancy and on the relationship between diabetes and cancer. There is also an inventory of currently used therapeutic tools and a review of novel therapeutic approaches like incretin-based therapies or sodium-glucose transporter-2 inhibitors. Additionally, the latest technological developments such as enhanced features for blood glucose meter or continuous and implantable glucose monitoring devices are included. Providing a concise but comprehensive update, this book will be essential to every clinician involved in the treatment of diabetes mellitus.

Personalized Predictive Modeling in Diabetes features state-of-the-art methodologies and algorithmic approaches which have been applied to predictive modeling of glucose concentration, ranging from simple autoregressive models of the CGM time series to multivariate nonlinear regression techniques of machine learning. Developments in the field have been analyzed with respect to: (i) feature set (univariate or multivariate), (ii) regression technique (linear or non-linear), (iii) learning mechanism (batch or sequential), (iv) development and testing procedure and (v) scaling properties. In addition, simulation models of meal-derived glucose absorption and insulin dynamics and kinetics are covered, as an integral part of glucose predictive models. This book will help engineers and clinicians to: select a regression technique which can capture both linear and non-linear dynamics in glucose metabolism in diabetes, and which exhibits good generalization performance under stationary and non-stationary conditions; ensure the scalability of the optimization algorithm (learning mechanism) with respect to the size of the dataset, provided that multiple days of patient monitoring are needed to obtain a reliable predictive model; select a features set which efficiently represents both spatial and temporal dependencies between the input variables and the glucose concentration; select simulation models of subcutaneous insulin absorption and meal absorption; identify an appropriate validation procedure, and identify realistic performance measures. Describes fundamentals of modeling techniques as applied to glucose control Covers model selection process and model validation Offers computer code on a companion website to show implementation of models and algorithms Features the latest developments in the field of diabetes predictive modeling

This advanced textbook is tailored for an introductory course in Systems Biology and is well-suited for biologists as well as engineers and computer scientists. It comes with student-friendly reading lists and a companion website featuring a short exam prep version of the book and educational modeling programs. The text is written in an easily accessible style and includes numerous worked examples and study questions in each chapter. For this edition, a section on medical systems biology has been included.