Modeling Methods For Medical Systems Biology
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| Author | : María Elena Álvarez-Buylla Roces |
| Publisher | : |
| Total Pages | : 258 |
| Release | : 2018 |
| Genre | : Bioinformatics |
| ISBN | : 9783319893556 |
This book contributes to better understand how lifestyle modulations can effectively halt the emergence and progression of human diseases. The book will allow the reader to gain a better understanding of the mechanisms by which the environment interferes with the bio-molecular regulatory processes underlying the emergence and progression of complex diseases, such as cancer. Focusing on key and early cellular bio-molecular events giving rise to the emergence of degenerative chronic disease, it builds on previous experience on the development of multi-cellular organisms, to propose a mathematical and computer based framework that allows the reader to analyze the complex interplay between bio-molecular processes and the (micro)-environment from an integrative, mechanistic, quantitative and dynamical perspective. Taking the wealth of empirical evidence that exists it will show how to build and analyze models of core regulatory networks involved in the emergence and progression of chronic degenerative diseases, using a bottom-up approach.
| Author | : Brian P. Ingalls |
| Publisher | : MIT Press |
| Total Pages | : 423 |
| Release | : 2022-06-07 |
| Genre | : Science |
| ISBN | : 0262545829 |
An introduction to the mathematical concepts and techniques needed for the construction and analysis of models in molecular systems biology. Systems techniques are integral to current research in molecular cell biology, and system-level investigations are often accompanied by mathematical models. These models serve as working hypotheses: they help us to understand and predict the behavior of complex systems. This book offers an introduction to mathematical concepts and techniques needed for the construction and interpretation of models in molecular systems biology. It is accessible to upper-level undergraduate or graduate students in life science or engineering who have some familiarity with calculus, and will be a useful reference for researchers at all levels. The first four chapters cover the basics of mathematical modeling in molecular systems biology. The last four chapters address specific biological domains, treating modeling of metabolic networks, of signal transduction pathways, of gene regulatory networks, and of electrophysiology and neuronal action potentials. Chapters 3–8 end with optional sections that address more specialized modeling topics. Exercises, solvable with pen-and-paper calculations, appear throughout the text to encourage interaction with the mathematical techniques. More involved end-of-chapter problem sets require computational software. Appendixes provide a review of basic concepts of molecular biology, additional mathematical background material, and tutorials for two computational software packages (XPPAUT and MATLAB) that can be used for model simulation and analysis.
| Author | : María Elena Álvarez-Buylla Roces |
| Publisher | : Springer |
| Total Pages | : 273 |
| Release | : 2018-08-03 |
| Genre | : Science |
| ISBN | : 3319893548 |
This book contributes to better understand how lifestyle modulations can effectively halt the emergence and progression of human diseases. The book will allow the reader to gain a better understanding of the mechanisms by which the environment interferes with the bio-molecular regulatory processes underlying the emergence and progression of complex diseases, such as cancer. Focusing on key and early cellular bio-molecular events giving rise to the emergence of degenerative chronic disease, it builds on previous experience on the development of multi-cellular organisms, to propose a mathematical and computer based framework that allows the reader to analyze the complex interplay between bio-molecular processes and the (micro)-environment from an integrative, mechanistic, quantitative and dynamical perspective. Taking the wealth of empirical evidence that exists it will show how to build and analyze models of core regulatory networks involved in the emergence and progression of chronic degenerative diseases, using a bottom-up approach.
| Author | : Markus W. Covert |
| Publisher | : CRC Press |
| Total Pages | : 367 |
| Release | : 2017-10-19 |
| Genre | : Technology & Engineering |
| ISBN | : 1498728472 |
For decades biology has focused on decoding cellular processes one gene at a time, but many of the most pressing biological questions, as well as diseases such as cancer and heart disease, are related to complex systems involving the interaction of hundreds, or even thousands, of gene products and other factors. How do we begin to understand this complexity? Fundamentals of Systems Biology: From Synthetic Circuits to Whole-cell Models introduces students to methods they can use to tackle complex systems head-on, carefully walking them through studies that comprise the foundation and frontier of systems biology. The first section of the book focuses on bringing students quickly up to speed with a variety of modeling methods in the context of a synthetic biological circuit. This innovative approach builds intuition about the strengths and weaknesses of each method and becomes critical in the book’s second half, where much more complicated network models are addressed—including transcriptional, signaling, metabolic, and even integrated multi-network models. The approach makes the work much more accessible to novices (undergraduates, medical students, and biologists new to mathematical modeling) while still having much to offer experienced modelers--whether their interests are microbes, organs, whole organisms, diseases, synthetic biology, or just about any field that investigates living systems.
| Author | : Nikolay V Dokholyan |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 360 |
| Release | : 2012-02-12 |
| Genre | : Science |
| ISBN | : 1461421454 |
Computational modeling is emerging as a powerful new approach to study and manipulate biological systems. Multiple methods have been developed to model, visualize, and rationally alter systems at various length scales, starting from molecular modeling and design at atomic resolution to cellular pathways modeling and analysis. Higher time and length scale processes, such as molecular evolution, have also greatly benefited from new breeds of computational approaches. This book provides an overview of the established computational methods used for modeling biologically and medically relevant systems.
| Author | : Ewart Carson |
| Publisher | : Elsevier |
| Total Pages | : 437 |
| Release | : 2000-12-31 |
| Genre | : Mathematics |
| ISBN | : 0080511902 |
Modelling Methodology for Physiology and Medicine offers a unique approach and an unprecedented range of coverage of the state-of-the-art, advanced modelling methodology that is widely applicable to physiology and medicine. The book opens with a clear and integrated treatment of advanced methodology for developing mathematical models of physiology and medical systems. Readers are then shown how to apply this methodology beneficially to real-world problems in physiology and medicine, such as circulation and respiration. - Builds upon and enhances the readers existing knowledge of modelling methodology and practice - Editors are internationally renowned leaders in their respective fields
| Author | : Darren J. Wilkinson |
| Publisher | : CRC Press |
| Total Pages | : 366 |
| Release | : 2018-12-07 |
| Genre | : Mathematics |
| ISBN | : 1351000896 |
Since the first edition of Stochastic Modelling for Systems Biology, there have been many interesting developments in the use of "likelihood-free" methods of Bayesian inference for complex stochastic models. Having been thoroughly updated to reflect this, this third edition covers everything necessary for a good appreciation of stochastic kinetic modelling of biological networks in the systems biology context. New methods and applications are included in the book, and the use of R for practical illustration of the algorithms has been greatly extended. There is a brand new chapter on spatially extended systems, and the statistical inference chapter has also been extended with new methods, including approximate Bayesian computation (ABC). Stochastic Modelling for Systems Biology, Third Edition is now supplemented by an additional software library, written in Scala, described in a new appendix to the book. New in the Third Edition New chapter on spatially extended systems, covering the spatial Gillespie algorithm for reaction diffusion master equation models in 1- and 2-d, along with fast approximations based on the spatial chemical Langevin equation Significantly expanded chapter on inference for stochastic kinetic models from data, covering ABC, including ABC-SMC Updated R package, including code relating to all of the new material New R package for parsing SBML models into simulatable stochastic Petri net models New open-source software library, written in Scala, replicating most of the functionality of the R packages in a fast, compiled, strongly typed, functional language Keeping with the spirit of earlier editions, all of the new theory is presented in a very informal and intuitive manner, keeping the text as accessible as possible to the widest possible readership. An effective introduction to the area of stochastic modelling in computational systems biology, this new edition adds additional detail and computational methods that will provide a stronger foundation for the development of more advanced courses in stochastic biological modelling.
| Author | : James A. Marcum |
| Publisher | : |
| Total Pages | : 252 |
| Release | : 2020-07-09 |
| Genre | : Systems biology |
| ISBN | : 9781536179606 |
Throughout most of the twentieth century, the biomedical model dominated healthcare. However, the biomedical model had its critics, who proposed alternative models to replace it. Eventually, biomedicine became fragmented at its foundations with a variety of approaches to its nature and practice. Medicine's current response to this fragmentation is to combine these disparate approaches into a single system--systems medicine. In the present book, I examine the shift, during the postgenomics era, from the biomedical model to systems medicine vis-à-vis systems biology, as well as the challenges facing systems medicine's implementation in the twenty-first century. The main goal of the present book is to provide a disciplinary framework for examining the rise of systems medicine, especially in terms of the incorporation of systems biology into the biomedical model. To realize that goal, the following questions are addressed. What is a disciplinary framework? And, why is this framework important for understanding systems biology and medicine? Briefly, a disciplinary framework represents the relational structure among disparate disciplines that support and ground a discipline and its corpus. For traditional biology and medicine, that framework consists of various disciplines within the biological and biomedical sciences, including physiology, neuroscience, pathology, and epidemiology--to name a few. For the present purpose, systems biology within the last several decades is reshaping the disciplinary framework of the biological and biomedical sciences, which is also responsible for the emergence of systems medicine. In addition, the challenges facing systems medicine, especially its operationalization and implementation with respect to medical education and practice, as well as research, are also explored.
| Author | : Daskalaki, Andriani |
| Publisher | : IGI Global |
| Total Pages | : 982 |
| Release | : 2008-11-30 |
| Genre | : Technology & Engineering |
| ISBN | : 1605660779 |
"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.
| Author | : Frédéric Cazals |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 333 |
| Release | : 2012-11-06 |
| Genre | : Mathematics |
| ISBN | : 364231208X |
Computational biology, mathematical biology, biology and biomedicine are currently undergoing spectacular progresses due to a synergy between technological advances and inputs from physics, chemistry, mathematics, statistics and computer science. The goal of this book is to evidence this synergy by describing selected developments in the following fields: bioinformatics, biomedicine and neuroscience. This work is unique in two respects - first, by the variety and scales of systems studied and second, by its presentation: Each chapter provides the biological or medical context, follows up with mathematical or algorithmic developments triggered by a specific problem and concludes with one or two success stories, namely new insights gained thanks to these methodological developments. It also highlights some unsolved and outstanding theoretical questions, with a potentially high impact on these disciplines. Two communities will be particularly interested in this book. The first one is the vast community of applied mathematicians and computer scientists, whose interests should be captured by the added value generated by the application of advanced concepts and algorithms to challenging biological or medical problems. The second is the equally vast community of biologists. Whether scientists or engineers, they will find in this book a clear and self-contained account of concepts and techniques from mathematics and computer science, together with success stories on their favorite systems. The variety of systems described represents a panoply of complementary conceptual tools. On a practical level, the resources listed at the end of each chapter (databases, software) offer invaluable support for getting started on a specific topic in the fields of biomedicine, bioinformatics and neuroscience.
