Computational Modeling Of Signaling Networks
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| Author | : Sangdun Choi |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 900 |
| Release | : 2010-08-09 |
| Genre | : Science |
| ISBN | : 1441957979 |
System Biology encompasses the knowledge from diverse fields such as Molecular Biology, Immunology, Genetics, Computational Biology, Mathematical Biology, etc. not only to address key questions that are not answerable by individual fields alone, but also to help in our understanding of the complexities of biological systems. Whole genome expression studies have provided us the means of studying the expression of thousands of genes under a particular condition and this technique had been widely used to find out the role of key macromolecules that are involved in biological signaling pathways. However, making sense of the underlying complexity is only possible if we interconnect various signaling pathways into human and computer readable network maps. These maps can then be used to classify and study individual components involved in a particular phenomenon. Apart from transcriptomics, several individual gene studies have resulted in adding to our knowledge of key components that are involved in a signaling pathway. It therefore becomes imperative to take into account of these studies also, while constructing our network maps to highlight the interconnectedness of the entire signaling pathways and the role of that particular individual protein in the pathway. This collection of articles will contain a collection of pioneering work done by scientists working in regulatory signaling networks and the use of large scale gene expression and omics data. The distinctive features of this book would be: Act a single source of information to understand the various components of different signaling network (roadmap of biochemical pathways, the nature of a molecule of interest in a particular pathway, etc.), Serve as a platform to highlight the key findings in this highly volatile and evolving field, and Provide answers to various techniques both related to microarray and cell signaling to the readers.
| Author | : Hamid Bolouri |
| Publisher | : Imperial College Press |
| Total Pages | : 341 |
| Release | : 2008 |
| Genre | : Medical |
| ISBN | : 1848162200 |
This book serves as an introduction to the myriad computational approaches to gene regulatory modeling and analysis, and is written specifically with experimental biologists in mind. Mathematical jargon is avoided and explanations are given in intuitive terms. In cases where equations are unavoidable, they are derived from first principles or, at the very least, an intuitive description is provided. Extensive examples and a large number of model descriptions are provided for use in both classroom exercises as well as self-guided exploration and learning. As such, the book is ideal for self-learning and also as the basis of a semester-long course for undergraduate and graduate students in molecular biology, bioengineering, genome sciences, or systems biology.
| Author | : Lan K. Nguyen |
| Publisher | : Springer Nature |
| Total Pages | : 387 |
| Release | : 2023-04-19 |
| Genre | : Science |
| ISBN | : 1071630083 |
This volume focuses on the computational modeling of cell signaling networks and the application of these models and model-based analysis to systems and personalized medicine. Chapters guide readers through various modeling approaches for signaling networks, new methods and techniques that facilitate model development and analysis, and new applications of signaling network modeling towards systems and personalized treatment of cancer. Written in the format of the highly successful Methods in Molecular Biology series, each chapter includes an introduction to the topic, lists necessary materials and methods, includes tips on troubleshooting and known pitfalls, and step-by-step, readily reproducible protocols. Authoritative and cutting-edge, Computational Modeling of Signaling Networks aims to benefit a wide spectrum of readers including researchers from the biological as well as computational systems biology communities.
| Author | : David Sterratt |
| Publisher | : Cambridge University Press |
| Total Pages | : 553 |
| Release | : 2023-10-05 |
| Genre | : Science |
| ISBN | : 1108483143 |
Learn to use computational modelling techniques to understand the nervous system at all levels, from ion channels to networks.
| Author | : |
| Publisher | : Academic Press |
| Total Pages | : 427 |
| Release | : 2012-05-31 |
| Genre | : Science |
| ISBN | : 0123884217 |
Computational methods are playing an ever increasing role in cell biology. This volume of Methods in Cell Biology focuses on Computational Methods in Cell Biology and consists of two parts: (1) data extraction and analysis to distill models and mechanisms, and (2) developing and simulating models to make predictions and testable hypotheses. - Focuses on computational methods in cell biology - Split into 2 parts--data extraction and analysis to distill models and mechanisms, and developing and simulating models to make predictions and testable hypotheses - Emphasizes the intimate and necessary connection with interpreting experimental data and proposing the next hypothesis and experiment
| Author | : Zhong Shao |
| Publisher | : Springer |
| Total Pages | : 436 |
| Release | : 2007-11-07 |
| Genre | : Computers |
| ISBN | : 9783540766360 |
This book constitutes the refereed proceedings of the 5th Asian Symposium on Programming Languages and Systems, APLAS 2007, held in Singapore, in November/December 2007. The 25 revised full papers presented together with three invited talks were carefully reviewed and selected from 84 submissions. The symposium addresses all issues in programming languages and systems - ranging from foundational to practical issues. The papers focus on a broad range of topics.
| Author | : Xuedong Liu |
| Publisher | : Humana Press |
| Total Pages | : 327 |
| Release | : 2013-01-31 |
| Genre | : Science |
| ISBN | : 9781617798344 |
Signaling networks are composed of numerous signaling pathways and each has its own intricate component parts. Signaling outputs are dynamic, extraordinarily complex and yet highly specific. In, Computational Modeling of Signaling Networks: Methods and Protocols, expert researchers in the field provide key techniques to study signaling networks. Focusing on Systems of ODEs, parameterization of signaling models, signaling pathways, mass-action kinetics and ODEs, and how to use modeling to plan experiments. Written in the highly successful Methods in Molecular BiologyTM series format, the chapters include the kind of detailed description and implementation advice that is crucial for getting optimal results in the laboratory. Thorough and intuitive, Computational Modeling of Signaling Networks: Methods and Protocols aids scientists in continuing study of how signaling networks behave in space and time to generate specific biological responses and how those responses impact biology and medicine.
| Author | : James Ferrell |
| Publisher | : Garland Science |
| Total Pages | : 285 |
| Release | : 2021-09-28 |
| Genre | : Science |
| ISBN | : 1000430731 |
How can we understand the complexity of genes, RNAs, and proteins and the associated regulatory networks? One approach is to look for recurring types of dynamical behavior. Mathematical models prove to be useful, especially models coming from theories of biochemical reactions such as ordinary differential equation models. Clever, careful experiments test these models and their basis in specific theories. This textbook aims to provide advanced students with the tools and insights needed to carry out studies of signal transduction drawing on modeling, theory, and experimentation. Early chapters summarize the basic building blocks of signaling systems: binding/dissociation, synthesis/destruction, and activation/inactivation. Subsequent chapters introduce various basic circuit devices: amplifiers, stabilizers, pulse generators, switches, stochastic spike generators, and oscillators. All chapters consistently use approaches and concepts from chemical kinetics and nonlinear dynamics, including rate-balance analysis, phase plane analysis, nullclines, linear stability analysis, stable nodes, saddles, unstable nodes, stable and unstable spirals, and bifurcations. This textbook seeks to provide quantitatively inclined biologists and biologically inclined physicists with the tools and insights needed to apply modeling and theory to interesting biological processes. Key Features: Full-color illustration program with diagrams to help illuminate the concepts Enables the reader to apply modeling and theory to the biological processes Further Reading for each chapter High-quality figures available for instructors to download
| Author | : Ina Koch |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 378 |
| Release | : 2010-10-21 |
| Genre | : Computers |
| ISBN | : 1849964742 |
The emerging, multi-disciplinary field of systems biology is devoted to the study of the relationships between various parts of a biological system, and computer modeling plays a vital role in the drive to understand the processes of life from an holistic viewpoint. Advancements in experimental technologies in biology and medicine have generated an enormous amount of biological data on the dependencies and interactions of many different molecular cell processes, fueling the development of numerous computational methods for exploring this data. The mathematical formalism of Petri net theory is able to encompass many of these techniques. This essential text/reference presents a comprehensive overview of cutting-edge research in applications of Petri nets in systems biology, with contributions from an international selection of experts. Those unfamiliar with the field are also provided with a general introduction to systems biology, the foundations of biochemistry, and the basics of Petri net theory. Further chapters address Petri net modeling techniques for building and analyzing biological models, as well as network prediction approaches, before reviewing the applications to networks of different biological classification. Topics and features: investigates the modular, qualitative modeling of regulatory networks using Petri nets, and examines an Hybrid Functional Petri net simulation case study; contains a glossary of the concepts and notation used in the book, in addition to exercises at the end of each chapter; covers the topological analysis of metabolic and regulatory networks, the analysis of models of signaling networks, and the prediction of network structure; provides a biological case study on the conversion of logical networks into Petri nets; discusses discrete modeling, stochastic modeling, fuzzy modeling, dynamic pathway modeling, genetic regulatory network modeling, and quantitative analysis techniques; includes a Foreword by Professor Jens Reich, Professor of Bioinformatics at Humboldt University and Max Delbrück Center for Molecular Medicine in Berlin. This unique guide to the modeling of biochemical systems using Petri net concepts will be of real utility to researchers and students of computational biology, systems biology, bioinformatics, computer science, and biochemistry.
| 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.
