Download or read book Identification Analysis and Control of Discrete and Continuous Models of Gene Regulation Networks written by Christian Breindl and published by . This book was released on 2016 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: A systems biological approach towards cellular networks promises a better understanding of how these systems work. The development of mathematical models is however inherently complicated, as the involved molecules and their interactions are mostly difficult to measure. Focusing on gene regulation networks, this work therefore intends to provide systems theoretic tools that support the process of model development and analysis in presence of such incomplete knowledge. The contributions are threefold. First, the problem of identifying interconnections between genes from noisy data is addressed. Existing solutions formulated in a discrete framework are reviewed and simplified significantly with the help of tools from convex optimization theory. Second, a novel method for model verification and discrimination is introduced. It is based on concepts from robust control theory and allows to quantify the capability of a model to reproduce experimentally observed stationary behaviors. As the proposed formalism only requires a vague knowledge about the interactions between the molecules, the method is intended to test and compare early modeling hypotheses. Third, the problem of controlling gene regulation networks in presence of qualitative information only is studied. Methods from discrete event systems theory are adapted to obtain stimulation strategies that will steer the network toward a desired attractor. The benefits of all contributions are illustrated with examples in the individual chapters.
Download or read book Emerging Research in the Analysis and Modeling of Gene Regulatory Networks written by Ivanov, Ivan V. and published by IGI Global. This book was released on 2016-06-06 with total page 437 pages. Available in PDF, EPUB and Kindle. Book excerpt: While technological advancements have been critical in allowing researchers to obtain more and better quality data about cellular processes and signals, the design and practical application of computational models of genomic regulation continues to be a challenge. Emerging Research in the Analysis and Modeling of Gene Regulatory Networks presents a compilation of recent and emerging research topics addressing the design and use of technology in the study and simulation of genomic regulation. Exploring both theoretical and practical topics, this publication is an essential reference source for students, professionals, and researchers working in the fields of genomics, molecular biology, bioinformatics, and drug development.
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 Analysis of Deterministic Cyclic Gene Regulatory Network Models with Delays written by Mehmet Eren Ahsen and published by Birkhäuser. This book was released on 2015-02-25 with total page 104 pages. Available in PDF, EPUB and Kindle. Book excerpt: This brief examines a deterministic, ODE-based model for gene regulatory networks (GRN) that incorporates nonlinearities and time-delayed feedback. An introductory chapter provides some insights into molecular biology and GRNs. The mathematical tools necessary for studying the GRN model are then reviewed, in particular Hill functions and Schwarzian derivatives. One chapter is devoted to the analysis of GRNs under negative feedback with time delays and a special case of a homogenous GRN is considered. Asymptotic stability analysis of GRNs under positive feedback is then considered in a separate chapter, in which conditions leading to bi-stability are derived. Graduate and advanced undergraduate students and researchers in control engineering, applied mathematics, systems biology and synthetic biology will find this brief to be a clear and concise introduction to the modeling and analysis of GRNs.
Download or read book Analysis of Combinatorial Gene Regulation with Thermodynamic Models written by Chieh-Chun Chen and published by . This book was released on 2010 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Transcriptional control is a key regulatory mechanism for cells to direct their destinies. A large number of transcription factors (TFs) could simultaneously bind to a regulatory sequence. With the constellation of TFs bound, the expression level of a target gene is usually determined by the combinatorial control of a number of TFs. The interactions among regulatory proteins and their regulatory sequences collectively form a regulatory network. A major challenge in the study of gene regulation is to identify the interaction relationships within a regulatory network and further to reconstruct gene regulatory networks. In this thesis, we developed an analytical method, Interaction-Identifier, to identify a thermodynamic model that best describes the form of TF-TF interaction among a set of TFs for every target gene. Applying this approach to time-course microarray data in mouse embryonic stem cells, we have inferred five interaction patterns among three regulators: Oct4, Sox2 and Nanog on ten target genes. We further proposed a computational framework, Network-Identifier, utilizing Interaction-Identifier, to reconstruct gene regulatory networks. Applied to five datasets of differentiating embryonic stem cells, Network-Identifier identified a gene regulatory network among 87 transcription regulator genes. This network suggests that Oct4, Sox2 and Klf4 indirectly repress lineage specific differentiation genes by activating transcriptional repressors of Ctbp2, Rest and Mtf2.
Download or read book Probabilistic Boolean Networks written by Ilya Shmulevich and published by SIAM. This book was released on 2010-01-21 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first comprehensive treatment of probabilistic Boolean networks, unifying different strands of current research and addressing emerging issues.
Download or read book System identification of Gene Regulatory Networks by Systematic Gene Perturbation Analysis written by Vida Abedi and published by . This book was released on 2009 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Systems Genetics written by Florian Markowetz and published by Cambridge University Press. This book was released on 2015-07-02 with total page 287 pages. Available in PDF, EPUB and Kindle. Book excerpt: Whereas genetic studies have traditionally focused on explaining heritance of single traits and their phenotypes, recent technological advances have made it possible to comprehensively dissect the genetic architecture of complex traits and quantify how genes interact to shape phenotypes. This exciting new area has been termed systems genetics and is born out of a synthesis of multiple fields, integrating a range of approaches and exploiting our increased ability to obtain quantitative and detailed measurements on a broad spectrum of phenotypes. Gathering the contributions of leading scientists, both computational and experimental, this book shows how experimental perturbations can help us to understand the link between genotype and phenotype. A snapshot of current research activity and state-of-the-art approaches to systems genetics are provided, including work from model organisms such as Saccharomyces cerevisiae and Drosophila melanogaster, as well as from human studies.
Download or read book Comparing Discrete Continuous and Hybrid Modelling Approaches of Gene Regulatory Networks written by Shahrad Jamshidi and published by . This book was released on 2012 with total page 130 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book A Mathematical Modeling and Approximation of Gene Expression Patterns by Linear and Quadratic Regulatory Relations and Analysis of Gene Networks written by and published by . This book was released on 2004 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis mainly concerns modeling, approximation and inference of gene regulatory dynamics on the basis of gene expression patterns. The dynamical behavior of gene expressions is represented by a system of ordinary di erential equations. We introduce a gene-interaction matrix with some nonlinear entries, in particular, quadratic polynomials of the expression levels to keep the system solvable. The model parameters are determined by using optimization. Then, we provide the time-discrete approximation of our time-continuous model. We analyze the approximating model under the aspect of stability. Finally, from the considered models we derive gene regulatory networks, discuss their qualitative features of the networks and provide a basis for analyzing networks with nonlinear connections.
Download or read book Modeling the Dynamics of Gene Regulatory Networks written by Aparna Das and published by . This book was released on 2012 with total page 121 pages. Available in PDF, EPUB and Kindle. Book excerpt: In order to describe the dynamic behavior of gene regulatory networks different formalisms have been introduced. In this thesis, we describe first the discrete approach of René Thomas and piecewise linear differential equations approach. Then we proposed a correspondence result between the two approaches and based on it we proposed an automatic computational technique to understand the global behavior of such complex systems using MAPLE programming language. The proposed code provides a way to compute the trajectories of the discrete version of a gene regulatory network model given an initial condition, in the same way as usual numerical algorithms give the "true" solution of a differential model from an initial condition. Knowing a discrete trajectory is less precise than knowing a true trajectory but correspondence theorems shows the link between the two approaches. Hence, it is a mathematical tool for analysing gene regulatory networks models. Finally, we illustrate both discrete and piecewise linear approaches, theircorrespondence and the use of our Maple code on a specific example: a mathematical model of the circadian clock. Our first two presented 8 and 4 variables models are the simplification of a model proposed by Leloup and Goldbeter. We deliberately choose to push the simplicity of the model as far as possible, focusing only on a few biological behaviors of interest. The hope is to get nevertheless the essential abstract causalities that govern these behaviors.
Download or read book Networks in Systems Biology written by Fabricio Alves Barbosa da Silva and published by Springer Nature. This book was released on 2020-10-03 with total page 381 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a range of current research topics in biological network modeling, as well as its application in studies on human hosts, pathogens, and diseases. Systems biology is a rapidly expanding field that involves the study of biological systems through the mathematical modeling and analysis of large volumes of biological data. Gathering contributions from renowned experts in the field, some of the topics discussed in depth here include networks in systems biology, the computational modeling of multidrug-resistant bacteria, and systems biology of cancer. Given its scope, the book is intended for researchers, advanced students, and practitioners of systems biology. The chapters are research-oriented, and present some of the latest findings on their respective topics.
Download or read book Gene Regulatory Networks written by and published by Academic Press. This book was released on 2020-06-06 with total page 448 pages. Available in PDF, EPUB and Kindle. Book excerpt: Gene Regulatory Networks, Volume 139 in the Current Topics in Developmental Biology series, highlights new advances in the field, with this new volume presenting interesting chapters written by an international board of authors. Topics in this release include Mouse hindbrain GRN, Xenopus endoderm GRN - organogenesis, Vertebrate limb GRN, The notochord gene regulatory network in chordate evolution: conservation and divergence from Ciona to vertebrates, Ciona early embryo GRNs, Boolean logic models, Modeling GRN response to morphogen gradient, GRN architecture, Theory of GRN evolution, Evolution of fly segmentation GRNs, GRN evolution in echinoderms, Evolution of network specificity, and more. Provides the authority and expertise of leading contributors from an international board of authors Presents the latest release in the Current Topics in Developmental Biology series Includes the latest information on gene regulatory networks
Download or read book Inference of Gene Regulatory Network Based on Gene Expression Dynamics in Response to Environmental Signals written by Yaqun Wang and published by . This book was released on 2015 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Thousands of genes are encoded on the genome and their products play important roles to cell survival, phenotypic characteristics of organisms and adaptive behaviors of organisms when environment changes. Detecting of particular sets of genes whose expressions are adaptive in response to environmental signals and identification of dynamic gene regulatory networks (GRN) can help us to understand the mechanistic base of gene-environment interactions and gene-gene interactions in a systematic way. However, it is a challenging work to analyze gene expression across two-dimensional spaces, time and environmental state. In this dissertation, we develop a functional clustering framework based on a mixture model to analyze time-course gene expression. The mathematical aspects of gene expression dynamics have been captured by Legendre polynomial and the impact of environment on gene expression has been considered jointly. We outline a number of quantitative testable hypotheses about the patterns of dynamic gene expression in changing environments and gene-environment interactions causing developmental differentiation. The method is illustrated with simulation studies and application on a real data set from a rabbit hemodynamic study.In addition, we propose two models for inference of GRN based on gene expression. We reform the Dynamic Bayesian Network (DBN) model for identification of GRN to overcome its limitation that evenly spaced measurements is required. The reformed model can accommodate to any possible irregularity and sparsity of time-course expression data by adaptively fitting gene expression curves, followed by a step of interpolating data at missing time points before conducting of DBN analysis. We also develop an ordinary differential equation (ODE) model to reconstruct GRNs based on functional clustering of genes. A set of ordinary differential equations are constructed to quantify the dynamic of GRN and the regulatory effects including positive and negative regulation are identified in a regression setting by using Smoothly Clipped Absolute Deviation (SCAD)-based variable selection. Both GRN models are equipped with unique power to integrate gene expression data from multiple environments and, therefore, provides an unprecedented tool to elucidate a comprehensive picture of GRN. By analyzing real data sets from a surgical study and through extensive simulation studies, the new models have been well demonstrated for their usefulness and utility.
Download or read book Handbook of Computational Molecular Biology written by Srinivas Aluru and published by CRC Press. This book was released on 2005-12-21 with total page 1108 pages. Available in PDF, EPUB and Kindle. Book excerpt: The enormous complexity of biological systems at the molecular level must be answered with powerful computational methods. Computational biology is a young field, but has seen rapid growth and advancement over the past few decades. Surveying the progress made in this multidisciplinary field, the Handbook of Computational Molecular Biology of
Download or read book Genomic Control Process written by Isabelle S. Peter and published by Academic Press. This book was released on 2015-01-21 with total page 461 pages. Available in PDF, EPUB and Kindle. Book excerpt: Genomic Control Process explores the biological phenomena around genomic regulatory systems that control and shape animal development processes, and which determine the nature of evolutionary processes that affect body plan. Unifying and simplifying the descriptions of development and evolution by focusing on the causality in these processes, it provides a comprehensive method of considering genomic control across diverse biological processes. This book is essential for graduate researchers in genomics, systems biology and molecular biology seeking to understand deep biological processes which regulate the structure of animals during development. - Covers a vast area of current biological research to produce a genome oriented regulatory bioscience of animal life - Places gene regulation, embryonic and postembryonic development, and evolution of the body plan in a unified conceptual framework - Provides the conceptual keys to interpret a broad developmental and evolutionary landscape with precise experimental illustrations drawn from contemporary literature - Includes a range of material, from developmental phenomenology to quantitative and logic models, from phylogenetics to the molecular biology of gene regulation, from animal models of all kinds to evidence of every relevant type - Demonstrates the causal power of system-level understanding of genomic control process - Conceptually organizes a constellation of complex and diverse biological phenomena - Investigates fundamental developmental control system logic in diverse circumstances and expresses these in conceptual models - Explores mechanistic evolutionary processes, illuminating the evolutionary consequences of developmental control systems as they are encoded in the genome
Download or read book Genomic Signal Processing written by Ilya Shmulevich and published by Princeton University Press. This book was released on 2014-09-08 with total page 314 pages. Available in PDF, EPUB and Kindle. Book excerpt: Genomic signal processing (GSP) can be defined as the analysis, processing, and use of genomic signals to gain biological knowledge, and the translation of that knowledge into systems-based applications that can be used to diagnose and treat genetic diseases. Situated at the crossroads of engineering, biology, mathematics, statistics, and computer science, GSP requires the development of both nonlinear dynamical models that adequately represent genomic regulation, and diagnostic and therapeutic tools based on these models. This book facilitates these developments by providing rigorous mathematical definitions and propositions for the main elements of GSP and by paying attention to the validity of models relative to the data. Ilya Shmulevich and Edward Dougherty cover real-world situations and explain their mathematical modeling in relation to systems biology and systems medicine. Genomic Signal Processing makes a major contribution to computational biology, systems biology, and translational genomics by providing a self-contained explanation of the fundamental mathematical issues facing researchers in four areas: classification, clustering, network modeling, and network intervention.
