Model Systems In Signal Transduction
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Model Systems In Signal Transduction
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Author : Shirish Shenolikar
language : en
Publisher: Lippincott Williams & Wilkins
Release Date : 1993
Model Systems In Signal Transduction written by Shirish Shenolikar and has been published by Lippincott Williams & Wilkins this book supported file pdf, txt, epub, kindle and other format this book has been release on 1993 with Science categories.
In this volume, distinguished investigators discuss their research on intracellular signal transduction in microorganisms. The findings presented aim to shed new light on fundamental processes of cell regulation in complex as well as simple organisms.
A Systems Biology Approach To Develop Models Of Signal Transduction Pathways
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Author : Zuyi Huang
language : en
Publisher:
Release Date : 2011
A Systems Biology Approach To Develop Models Of Signal Transduction Pathways written by Zuyi Huang and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011 with categories.
Mathematical models of signal transduction pathways are characterized by a large number of proteins and uncertain parameters, yet only a limited amount of quantitative data is available. The dissertation addresses this problem using two different approaches: the first approach deals with a model simplification procedure for signaling pathways that reduces the model size but retains the physical interpretation of the remaining states, while the second approach deals with creating rich data sets by computing transcription factor profiles from fluorescent images of green-fluorescent-protein (GFP) reporter cells. For the first approach a model simplification procedure for signaling pathway models is presented. The technique makes use of sensitivity and observability analysis to select the retained proteins for the simplified model. The presented technique is applied to an IL-6 signaling pathway model. It is found that the model size can be significantly reduced and the simplified model is able to adequately predict the dynamics of key proteins of the signaling pathway. An approach for quantitatively determining transcription factor profiles from GFP reporter data is developed as the second major contribution of this work. The procedure analyzes fluorescent images to determine fluorescence intensity profiles using principal component analysis and K-means clustering, and then computes the transcription factor concentration from the fluorescence intensity profiles by solving an inverse problem involving a model describing transcription, translation, and activation of green fluorescent proteins. Activation profiles of the transcription factors NF-kB, nuclear STAT3, and C/EBPß are obtained using the presented approach. The data for NF-kB is used to develop a model for TNF-a signal transduction while the data for nuclear STAT3 and C/EBPß is used to verify the simplified IL-6 model. Finally, an approach is developed to compute the distribution of transcription factor profiles among a population of cells. This approach consists of an algorithm for identifying individual fluorescent cells from fluorescent images, and an algorithm to compute the distribution of transcription factor profiles from the fluorescence intensity distribution by solving an inverse problem. The technique is applied to experimental data to derive the distribution of NF-kB concentrations from fluorescent images of a NF-kB GFP reporter system.
Systems Biology Of Cell Signaling
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Author : James E. Ferrell
language : en
Publisher: Garland Science
Release Date : 2021-09-28
Systems Biology Of Cell Signaling written by James E. Ferrell and has been published by Garland Science this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-28 with Science categories.
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
Computational Modeling Of Signaling Networks
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Author : Lan K. Nguyen
language : en
Publisher: Springer Nature
Release Date : 2023-04-19
Computational Modeling Of Signaling Networks written by Lan K. Nguyen and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-04-19 with Science categories.
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.
Understanding Signal Transduction In Biological Systems With Network Based Dynamic Modeling
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Author : Xiao Gan
language : en
Publisher:
Release Date : 2019
Understanding Signal Transduction In Biological Systems With Network Based Dynamic Modeling written by Xiao Gan and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with categories.
Omplex biological systems are composed of simple, low-level elements. A promising avenue toward understanding how system-level behavior arises from the interactions of lower-level components is network-based dynamical modeling. For example, dynamic modeling of molecular interaction networks can capture cell behavior or phenotype as an emergent property that arises from the dynamics of the system. In a dynamic model, a node is associated with a state and a regulatory function that describes its time-evolution. The attractors (long-time behavior) of a network-based dynamical model represent significant biological phenotypes, e.g. cell fates. It is therefore important to know the attractors of a network model, so that one may design interventions to avoid undesired attractors and keep the system in the desired attractor. The challenge for determining the complete dynamic repertoire is the huge state space size. The unifying theme of my dissertation research is to understand signal transduction in complex biological systems. All of my projects used discrete dynamic modeling, which can recapitulate biological knowledge with minimal requirement of kinetic parameterization, and is thus simple enough to apply on large biological systems. In my first project I analyzed the attractor landscape of a 70-node multi-level biological network model. This model described plant guard cell signaling during the process in which microscopic pores on the surface of the leaves (called stomata) open in response to light of different wavelength. Due to the size of the network and the multiple states of a portion of the nodes, this model has a huge state space (~1031 states). Using a combination of network reduction analysis techniques, I found the models complete dynamic repertoire, revealing the stability of signal transduction in the stomatal opening process. In a following project, I developed a general method to automatically identify the attractors of any finite discrete model, based on a Boolean method developed by our group previously. The idea is to exploit an expanded network representation that incorporates regulatory rules into the interaction network. A certain type of subgraph of the expanded network determines a trap subspace of the state space (i.e. a subspace which if the system enters, it cannot escape). These motifs are the dynamic cores of a model. Iterative identification of stable motifs yields the attractors of the system. The method finds not only steady states, but also complex (oscillating) attractors. I showed this mathematically, and validated it on synthetic network ensembles, and on a list of existing multi-level models in the literature. My third project is modeling plant response to environmental stress, in collaboration with wet-bench biologists. Plants close their stomata in response to high CO2 concentration or to phytohormones such as ABA (abscisic acid) induced by drought. We aim to understand how different signaling components participate in the crosstalk of ABA and CO2 in inducing stomatal closure. We are also interested in the different signaling mechanisms involving canonical and non-canonical subunits of the G-protein (a membrane protein involved in many types of trans-membrane signal transduction). The network model integrates previous work on ABA signaling with existing knowledge on CO2 signaling, and predicts necessary regulations of the G-protein based on necessary conditions for the model to be consistent with experimental observations. We explain the mechanism by which different signals induce closure by our motifs analysis. The model is also predicting interesting closure patterns under interventions. The predictions will be assessed experimentally by our collaborative team. In summary, my dissertation research has provided a general way to analyze complex discrete dynamic models, and has expanded the understanding of plant responses to environmental stress.
Analysis Of Diverse Signal Transduction Pathways Using The Genetic Model System Caenorhabditis Elegans
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Author : Celine Moorman
language : en
Publisher:
Release Date : 2003
Analysis Of Diverse Signal Transduction Pathways Using The Genetic Model System Caenorhabditis Elegans written by Celine Moorman and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003 with categories.
Cellular Signal Processing
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Author : Friedrich Marks
language : en
Publisher: Garland Science
Release Date : 2008-11-14
Cellular Signal Processing written by Friedrich Marks and has been published by Garland Science this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-11-14 with Science categories.
Cellular Signal Processing is intended for use in signal transduction courses for undergraduate and graduate students. It offers a unifying view of cell signaling that is based on the concept of protein interactions acting as sophisticated data processing networks that govern intracellular and extracellular communication. The content is guided by three major principles that are central to signal transduction: the protein network, its energy supply, and its evolution. It includes coverage of all important aspects of cell signaling, ranging from prokaryotic signal transduction to neuronal signaling. It also highlights the clinical aspects of cell signaling in health and disease.
Intracellular Signaling Mediators In The Circulatory And Ventilatory Systems
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Author : Marc Thiriet
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-09-26
Intracellular Signaling Mediators In The Circulatory And Ventilatory Systems written by Marc Thiriet and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-09-26 with Science categories.
The volumes in this authoritative series present a multidisciplinary approach to modeling and simulation of flows in the cardiovascular and ventilatory systems, especially multiscale modeling and coupled simulations. The cardiovascular and respiratory systems are tightly coupled, as their primary function is to supply oxygen to and remove carbon dioxide from the body's cells. Because physiological conduits have deformable and reactive walls, macroscopic flow behavior and prediction must be coupled to phenomenological models of nano- and microscopic events in a corrector scheme of regulated mechanisms when the vessel lumen caliber varies markedly. Therefore, investigation of flows of blood and air in physiological conduits requires an understanding of the biology, chemistry, and physics of these systems together with the mathematical tools to describe their functioning. Volume 4 is devoted to major sets of intracellular mediators that transmit signals upon stimulation of cell-surface receptors. Activation of signaling effectors triggers the release of substances stored in cellular organelles and/or gene transcription and protein synthesis. Complex stages of cell signaling can be studied using proper mathematical models, once the role of each component is carefully handled. Volume 4 also reviews various categories of cytosolic and/or nuclear mediators and illustrates some major signal transduction pathways, such as NFkappaB axis, oxygen sensing, and mechanotransduction.
Mathematical Modelling Of The Jak Stat1 Signal Transduction Pathway
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Author : Stephan Beirer
language : en
Publisher:
Release Date : 2007
Mathematical Modelling Of The Jak Stat1 Signal Transduction Pathway written by Stephan Beirer and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with categories.
The Jak/Stat1 signalling pathway is a prototypical example of a direct signal transduction system which relays external signals directly from the receptor located at the cellular membrane to its nuclear target genes. This work seeks to acquire a comprehensive theoretical understanding of the quantitative and qualitative aspects of Jak/Stat1 signal transduction, using a combination of different theoretical approaches and methods together with specific experimental measurements. This thesis consists of three independent parts. In part I the biological system is introduced and a detailed model of Jak/Stat1 signalling is presented. The estimation of the model parameters is demonstrated. The model structure and the parameter values are verified using independent experimental measurements. Using numerical model simulations we investigate the dynamics of Stat1 signalling and examine the control properties of the system processes. Part II of this thesis presents a general treatment of Jak/Stat signal transduction using analytical methods. We reduce the complexity of the detailed Jak/Stat model and obtain a simplified linear core model. Using this core model we derive a relation between the lifetimes of the subcellular Stat fractions and their steady state concentrations. Furthermore we model general signal transduction systems as networks of linear state transitions and derive a rule relating the distribution of control among the network processes with the steady state occupancy of the specific network states. In the third part of this work the theoretical predictions of part I and II about the control properties of the subcellular transport processes of the Stat1 molecules are examined using experimental data from different Stat1 transport mutants. The changed phenotypes of these mutant proteins are compared to different model simulations. The high regulatory potential of the shuttling process of inactive Stat1 protein predicted by the model is confirmed.
A New Simulation Framework For Modeling Signal Transduction Pathways
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Author : Smitha Cheruku
language : en
Publisher:
Release Date : 2006
A New Simulation Framework For Modeling Signal Transduction Pathways written by Smitha Cheruku and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006 with Cellular signal transduction categories.