Download or read book Computational Modeling of Signaling Networks written by Lan K. Nguyen and published by Springer Nature. This book was released on 2023-04-19 with total page 387 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Computational Modeling Of Gene Regulatory Networks A Primer written by Hamid Bolouri and published by World Scientific Publishing Company. This book was released on 2008-08-13 with total page 341 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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./a

Download or read book Computational Modeling of Cell Signaling Network Using Hill Function and Markov Chain Monte Carlo Methods written by Xin Yang Davis and published by . This book was released on 2010 with total page 126 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Systems Biology for Signaling Networks written by Sangdun Choi and published by Springer Science & Business Media. This book was released on 2010-08-09 with total page 900 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Computational Modeling of Genetic and Biochemical Networks written by James M. Bower and published by MIT Press. This book was released on 2001 with total page 386 pages. Available in PDF, EPUB and Kindle. Book excerpt: How new modeling techniques can be used to explore functionally relevant molecular and cellular relationships.

Download or read book Computational Modeling of the EGF Receptor Signaling Network written by Fang Zheng and published by . This book was released on 2004 with total page 150 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Computational Systems Biology written by Christina Kiel and published by Elsevier Inc. Chapters. This book was released on 2013-11-26 with total page 43 pages. Available in PDF, EPUB and Kindle. Book excerpt: This chapter brings mammalian signal transduction to the center of quantitative and integrative sciences. Historically imbedded within human physiology, thanks to proteomics, interactomics, and molecular biology approaches, signaling is now far beyond the “black box” principle. However, despite the large amount of data available, we still have only limited insight into general design principles, and we lack knowledge on how cell type-specific signaling is achieved. Here, we summarize recent efforts in elucidating cell type-specific signaling, and in particular the role of protein abundances, signaling complexes and modules. We further discuss the potential of using synthetic biology approaches to decipher signaling networks. All of this is discussed in light of complementary quantitative mathematical modeling approaches. Signaling, more than any other discipline, needs computational biology to capture the dynamic systems behavior, and to reach its final goal: to be truly predictive for both the physiological and disease perturbed cellular conditions.

Download or read book Principles of Computational Modelling in Neuroscience written by David Sterratt and published by Cambridge University Press. This book was released on 2023-10-05 with total page 553 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn to use computational modelling techniques to understand the nervous system at all levels, from ion channels to networks.

Download or read book Modellierung Logischer Signalnetzwerke Mittels Antwortmengenprogrammierung written by and published by . This book was released on 2014 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Deciphering the functioning of biological networks is one of the central tasks in systems biology. In particular, signal transduction networks are crucial for the understanding of the cellular response to external and internal perturbations. Importantly, in order to cope with the complexity of these networks, mathematical and computational modeling is required. We propose a computational modeling framework in order to achieve more robust discoveries in the context of logical signaling networks. More precisely, we focus on modeling the response of logical signaling networks by means of automated reasoning using Answer Set Programming (ASP). ASP provides a declarative language for modeling various knowledge representation and reasoning problems. Moreover, available ASP solvers provide several reasoning modes for assessing the multitude of answer sets. Therefore, leveraging its rich modeling language and its highly efficient solving capacities, we use ASP to address three challenging problems in the context of logical signaling networks: learning of (Boolean) logical networks, experimental design, and identification of intervention strategies. Overall, the contribution of this thesis is three-fold. Firstly, we introduce a mathematical framework for characterizing and reasoning on the response of logical signaling networks. Secondly, we contribute to a growing list of successful applications of ASP in systems biology. Thirdly, we present a software providing a complete pipeline for automated reasoning on the response of logical signaling networks.

Download or read book Programming Languages and Systems written by Zhong Shao and published by Springer. This book was released on 2007-11-07 with total page 436 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Modeling Analysis and Network Identification of Cancer Signal Transduction Networks written by Katharine Veronica Rogers and published by . This book was released on 2016 with total page 174 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cancer involves the dysregulation of multiple signaling pathways in which computational modeling can be applied to understand complex network responses. A computational modeling approach can be used to determine the development of drug resistance in cancers, predict combination therapies, and determine individualized treatment for cancer patients. To this end we have employed mechanistic modeling to a variety of cancer networks. In Chapter 1, we review current methods and progress toward using computational methods for cancer biology. Cancer is no longer considered one gene one disease and computational modeling is an important tool in understanding the development of many cancer types. In Chapter 2, we constructed a mechanistic model of the development of castration resistant prostate cancer (CRPC). Analysis of the model suggested that simultaneously targeting the PI3K and MAPK pathways in addition to anti-androgen therapies could be an effective treatment for CRPC. We experimentally tested this hypothesis in both androgen dependent prostate cancer (ADPC) LNCaP cell lines and LNCaP derived CRPC C4-2 cells using three inhibitors: the androgen receptor inhibitor MDV3100 (enzalutamide), the Raf kinase inhibitor sorafenib, and the PI3K inhibitor LY294002. Consistent with model predictions, cell viability decreased at 72 hrs in the dual and triple inhibition cases in both the LNCaP and C4-2 cell lines. In Chapter 3, we look at the importance of network identification in mechanistic modeling of cancer networks. Cancer is a complex disease and complete biological knowledge of the system is often unknown. Using a small three node protein example we were able to obtain a correct model structure with no a priorii knowledge of the system. We then applied this method to determine transcription factor network structures for six leukemia cell lines: K562, HL60, NB4, U937, HL60 R38+ and HL60 R38-. Starting with an initial best guess model structure we were able to determine additional network modifications for each cell line to improve model fit of experimental data. Potential future directions and closing remarks are offered in Chapter 4. Taken together, the results of these studies demonstrated that computational modeling can aid in identifying therapeutic targets and combination treatments for cancer. Also, the use of computational modeling can improve cancer network identification in the absence of complete biological knowledge.

Download or read book Systems Biology in Drug Discovery and Development written by Qing Yan and published by Humana Press. This book was released on 2010-09-21 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Due to the failing “one-drug-fits-all” model, it has become increasingly necessary to develop personalized medicine that treats whole systems and brings the right drug to the right patient with the right dosages. In Systems Biology in Drug Discovery and Development: Methods and Protocols, leading experts provide a practical, state-of-the-art, and holistic view of the translation of systems biology into better drug discovery and personalized medical practice. While the first part of the book describes cutting-edge technologies and methods in the field, the second part illustrates how the technologies can be applied in science for disease understanding and therapeutic discovery. As a volume in the highly successful Methods in Molecular BiologyTM series, this collection provides the kind of detailed description and implementation advice that is crucial for getting optimal results. Authoritative and up-to-date, Systems Biology in Drug Discovery and Development: Methods and Protocols covers topics from fundamental concepts to advanced technologies in order to best serve biomedical students and professionals at all levels who are interested in vital integrative studies in molecular biology, genetics, bioinformatics, bioengineering, biochemistry, physiology, pathology, microbiology, immunology, pharmacology, toxicology, drug discovery, and clinical medicine.

Download or read book Rule based Computational Modeling of Modular Signaling Protein Interactions written by and published by . This book was released on 2004 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Intracellular signal transduction pathways are comprised of complex interactions among cellular proteins and other biomolecules. The structures of signaling proteins/enzymes are often modular, with conserved domains that carry out specific interactions or catalytic functions, and their core activities are dictated through coordinated intra- and inter-molecular interactions. In collaboration with Prof. James Faeder (Computational Biology, University of Pittsburgh), we have applied a computational algorithm for generating large networks of kinetic equations based on a much smaller set of mechanistic rules. Using this rule-based approach, we have formulated kinetic models that account for the modular domain structure of specific signaling proteins, including Shp2 (Src homology-2 domain containing protein tyrosine phosphatase 2), PI3K (phosphatidilinositol-3-kinase) regulatory subunit, and SH2-B (a Jak2 kinase activating adaptor protein). Analysis of these models reveals the combinatorial possibilities of reactions and interactions that might occur in living cells. We propose here to extend this rule-based approach for larger pathway models through systematic reduction and integration of small subsystem models.

Download or read book Modeling and Analysis of Signal Transduction Networks written by and published by . This book was released on 2016 with total page 232 pages. Available in PDF, EPUB and Kindle. Book excerpt: Biological pathways, such as signaling networks, are a key component of biological systems of each living cell. In fact, malfunctions of signaling pathways are linked to a number of diseases, and components of signaling pathways are used as potential drug targets. Elucidating the dynamic behavior of the components of pathways, and their interactions, is one of the key research areas of systems biology. Biological signaling networks are characterized by a large number of components and an even larger number of parameters describing the network. Furthermore, investigations of signaling networks are characterized by large uncertainties of the network as well as limited availability of data due to expensive and time-consuming experiments. As such, techniques derived from systems analysis, e.g., sensitivity analysis, experimental design, and parameter estimation, are important tools for elucidating the mechanisms involved in signaling networks. This Special Issue contains papers that investigate a variety of different signaling networks via established, as well as newly developed modeling and analysis techniques.

Download or read book Systems Biology of Cell Signaling written by James Ferrell and published by Garland Science. This book was released on 2021-09-28 with total page 285 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Download or read book Computational Stem Cell Biology written by Patrick Cahan and published by Humana. This book was released on 2019-05-07 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume details methods and protocols to further the study of stem cells within the computational stem cell biology (CSCB) field. Chapters are divided into four sections covering the theory and practice of modeling of stem cell behavior, analyzing single cell genome-scale measurements, reconstructing gene regulatory networks, and metabolomics. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls. Authoritative and cutting-edge, Computational Stem Cell Biology: Methods and Protocols will be an invaluable guide to researchers as they explore stem cells from the perspective of computational biology.

Download or read book Modeling in Systems Biology written by Ina Koch and published by Springer Science & Business Media. This book was released on 2010-10-21 with total page 378 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.