Download or read book Topology and Dynamics of an Artificial Genetic Regulatory Network Model written by P. Dwight Kuo and published by . This book was released on 2005 with total page 278 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Computational Genetic Regulatory Networks Evolvable Self organizing Systems written by Johannes F. Knabe and published by Springer. This book was released on 2012-08-14 with total page 125 pages. Available in PDF, EPUB and Kindle. Book excerpt: Genetic Regulatory Networks (GRNs) in biological organisms are primary engines for cells to enact their engagements with environments, via incessant, continually active coupling. In differentiated multicellular organisms, tremendous complexity has arisen in the course of evolution of life on earth. Engineering and science have so far achieved no working system that can compare with this complexity, depth and scope of organization. Abstracting the dynamics of genetic regulatory control to a computational framework in which artificial GRNs in artificial simulated cells differentiate while connected in a changing topology, it is possible to apply Darwinian evolution in silico to study the capacity of such developmental/differentiated GRNs to evolve. In this volume an evolutionary GRN paradigm is investigated for its evolvability and robustness in models of biological clocks, in simple differentiated multicellularity, and in evolving artificial developing 'organisms' which grow and express an ontogeny starting from a single cell interacting with its environment, eventually including a changing local neighbourhood of other cells. These methods may help us understand the genesis, organization, adaptive plasticity, and evolvability of differentiated biological systems, and may also provide a paradigm for transferring these principles of biology's success to computational and engineering challenges at a scale not previously conceivable.
Download or read book Evolutionary Computation in Gene Regulatory Network Research written by Hitoshi Iba and published by John Wiley & Sons. This book was released on 2016-01-20 with total page 464 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introducing a handbook for gene regulatory network research using evolutionary computation, with applications for computer scientists, computational and system biologists This book is a step-by-step guideline for research in gene regulatory networks (GRN) using evolutionary computation (EC). The book is organized into four parts that deliver materials in a way equally attractive for a reader with training in computation or biology. Each of these sections, authored by well-known researchers and experienced practitioners, provides the relevant materials for the interested readers. The first part of this book contains an introductory background to the field. The second part presents the EC approaches for analysis and reconstruction of GRN from gene expression data. The third part of this book covers the contemporary advancements in the automatic construction of gene regulatory and reaction networks and gives direction and guidelines for future research. Finally, the last part of this book focuses on applications of GRNs with EC in other fields, such as design, engineering and robotics. • Provides a reference for current and future research in gene regulatory networks (GRN) using evolutionary computation (EC) • Covers sub-domains of GRN research using EC, such as expression profile analysis, reverse engineering, GRN evolution, applications • Contains useful contents for courses in gene regulatory networks, systems biology, computational biology, and synthetic biology • Delivers state-of-the-art research in genetic algorithms, genetic programming, and swarm intelligence Evolutionary Computation in Gene Regulatory Network Research is a reference for researchers and professionals in computer science, systems biology, and bioinformatics, as well as upper undergraduate, graduate, and postgraduate students. Hitoshi Iba is a Professor in the Department of Information and Communication Engineering, Graduate School of Information Science and Technology, at the University of Tokyo, Toyko, Japan. He is an Associate Editor of the IEEE Transactions on Evolutionary Computation and the journal of Genetic Programming and Evolvable Machines. Nasimul Noman is a lecturer in the School of Electrical Engineering and Computer Science at the University of Newcastle, NSW, Australia. From 2002 to 2012 he was a faculty member at the University of Dhaka, Bangladesh. Noman is an Editor of the BioMed Research International journal. His research interests include computational biology, synthetic biology, and bioinformatics.
Download or read book Computational Modeling of Gene Regulatory Networks written by Hamid Bolouri and published by Imperial College Press. This book was released on 2008 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.
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 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 Modular Studies of Gene Networks written by Farren Justin Isaacs and published by . This book was released on 2003 with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract: The deduction of phenotypic cellular responses from the structure and behavior of complex gene regulatory networks is one of the defining challenges of systems biology. This goal will require a detailed understanding of the modular components that constitute whole-genome regulation. This thesis explores computational and experimental techniques for studying the expression dynamics of gene regulatory networks. We first pursued an integrated approach, combining experimental work with a quantitative theoretical model, to analyze and describe the dynamics of a simple, isolated genetic module, an in vivo autocatalytic single-gene network. The network exhibited bistable expression states, which validated predictions arising from a system-specific mathematical description of the underlying biochemistry. Since the experiments revealed large fluctuations in the expression states, we augmented the model with noise terms and obtained striking agreement between model and experimental results. This work demonstrates that isolated gene networks, coupled with quantitative models which account for the stochastic nature of gene expression, can elucidate key properties of functional genetic modules. Next, we turned to the design of artificial genetic networks. Cellular AND/OR logic gates were constructed from well-characterized components that uniquely respond to applied stimuli. In contrast to the autocatalytic gene network study, logic gates were constructed to achieve simple, predetermined function setting the stage for detailed characterization. Finally, we designed and utilized artificial RNA control modules as regulatory components of gene networks. These systems functioned as catalytic activators and repressors to regulate post-transcriptional gene expression. This universal type of switching strategy can target the expression of any prokaryotic gene and may be extended as a post-transcriptional regulator in eukaryotes. These simple networks represent a first step towards constructing a framework of logical cellular control, whereby biological processes can be controlled or monitored at the protein, DNA and RNA levels. Such a framework can lead to the modular dissection of whole cell regulatory networks.
Download or read book Application of Machine Learning to Mapping and Simulating Gene Regulatory Networks written by Hien-haw Liow and published by . This book was released on 2015 with total page 166 pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation explores, proposes, and examines methods of applying modernmachine learning and Bayesian statistics in the quantitative and qualitative modeling of gene regulatory networks using high-throughput gene expression data. A semi-parametric Bayesian model based on random forest is developed to infer quantitative aspects of gene regulation relations; a parametric model is developed to predict geneexpression levels solely from genotype information. Simulation of network behavior is shown to complement regression analysis greatly in capturing the dynamics of gene regulatory networks. Finally, as an application and extension of novel approaches in gene expression analysis, new methods of discovering topological structure of gene regulatory networks are developed and shown to provide improvement over existing methods.
Download or read book Systems Immunology and Infection Microbiology written by Bor-Sen Chen and published by Academic Press. This book was released on 2021-03-16 with total page 673 pages. Available in PDF, EPUB and Kindle. Book excerpt: Systems Immunology and Infection Microbiology provides a large amount of biological system models, diagrams and flowcharts to illustrate development procedures and help users understand the results of systems immunology and infection microbiology. Chapters discuss systems immunology, systems infection microbiology, systematic inflammation and immune responses in restoration and regeneration process, systems' innate and adaptive immunity in infection process, systematic genetic and epigenetic pathogenic/defensive mechanism during bacterial infection on human cells is introduced, and the systematic genetic and epigenetic pathogenic/defensive mechanisms during viral infection on human cells. This book provides new big data-driven and systems-driven systems immunology and infection microbiology to researchers applying systems biology and bioinformatics in their work. It is also invaluable to several members of biomedical field who are interested in learning more about those approaches. Encompasses one applicable example in every chapter to illustrate the solution procedure from big data mining, network modeling, host/pathogen cross-talk detection, drug target identification and systems drug design Presents flowcharts to represent the development procedure of systematic immunology and infection in a very clear format Contains 100 color diagrams to help readers understand the related biological networks, their corresponding mechanisms, and significant network biomarkers for therapeutic drug design
Download or read book Topological Properties of Eukaryotic Gene Regulatory Networks written by Zachary Wilberforce Ouma and published by . This book was released on 2017 with total page 161 pages. Available in PDF, EPUB and Kindle. Book excerpt: Secondly, I describe the architectural organization and associated emergent topological properties of GRNs that describe protein-DNA interactions (PDIs) in several model eukaryotes. By analyzing GRN connectivity, results presented here show that the anticipated scale-free network architectures are characterized by organism-specific power law scaling exponents. These exponents are independent of the fraction of the GRN experimentally sampled, enabling prediction of properties of the complete GRN for an organism. I further demonstrate that the exponents describe inequalities in TF-target gene recognition across GRNs. These observations have the important biological implication that they predict the existence of an intrinsic organism-specific trans and/or cis regulatory landscape that constrains GRN topologies. Consequently, architectural GRN organization drives not only phenotypic plasticity within a species, but is also likely implicated in species-specific phenotype. Lastly, I discuss future perspectives of this work. I briefly present models that can be used to capture GRN dynamics. I focus on a class of logical models— the Boolean network model, and propose a framework for constructing and implementing a dynamic model that captures the complex regulatory repertoire of eukaryotic organisms.
Download or read book A Study of Small Gene Regulatory Networks written by Sarah Robin Stockwell and published by . This book was released on 2010 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Gene regulatory networks, like any evolving biological system, are subject to potentially damaging mutations. Much work has been done to study what types of networks are more robust to node deletions (knockouts of entire genes). Less well understood, however, is the question of which networks best maintain consistent behavior in the face of smaller mutations that affect binding affinity, protein half-life, and other regulatory parameters. Such mutations have subtler effects than whole-gene knockouts do, but because they are far more common than knockout mutations, their impact on network evolution may be substantial. The first chapter investigates the expression patterns of simulated gene regulatory networks as these types of parameters are varied, and explores which topologies allow the networks to "ignore" parameterchanging mutations and maintain their expression patterns relatively unchanged. In the simulations, networks containing mutual repression feedback consistently displayed a more robust response to simulated mutation. The presence of this variety of feedback in well-studied developmental regulatory networks suggests that it may be a widespread mechanism for reducing the phenotypic consequences of both noise and mutational perturbations. The second chapter also uses feedback loop module networks as a means to investigate and compare modeling approaches. It describes an algorithm to infer the best Boolean representation of the differential equation network models, as well as metrics for measuring how closely the Boolean model approached the dynamics of the continuous one. Using these tools allowed testing of the "Booleanizability" of networks containing mutual-activator and mutual-repressor feedback loops. The investigation revealed that Boolean models are better approximations of networks with repressor loops than of those without them, and this is explained in terms of the characteristics explored in the investigation of network robustness. Chapter 3 contains a model of the gap genes in Drosophila melanogaster, based on published experimental findings on the interactions among these genes and their products. The mechanistic mathematical model of gap gene expression was fitted to experimental data and placed in the context of other gap gene models. The chapter discusses the advantages and limitations of the various modeling techniques that have been employed for this system.
Download or read book Artificial Chemistries written by Wolfgang Banzhaf and published by MIT Press. This book was released on 2024-03-19 with total page 572 pages. Available in PDF, EPUB and Kindle. Book excerpt: An introduction to the fundamental concepts of the emerging field of Artificial Chemistries, covering both theory and practical applications. The field of Artificial Life (ALife) is now firmly established in the scientific world, but it has yet to achieve one of its original goals: an understanding of the emergence of life on Earth. The new field of Artificial Chemistries draws from chemistry, biology, computer science, mathematics, and other disciplines to work toward that goal. For if, as it has been argued, life emerged from primitive, prebiotic forms of self-organization, then studying models of chemical reaction systems could bring ALife closer to understanding the origins of life. In Artificial Chemistries (ACs), the emphasis is on creating new interactions rather than new materials. The results can be found both in the virtual world, in certain multiagent systems, and in the physical world, in new (artificial) reaction systems. This book offers an introduction to the fundamental concepts of ACs, covering both theory and practical applications. After a general overview of the field and its methodology, the book reviews important aspects of biology, including basic mechanisms of evolution; discusses examples of ACs drawn from the literature; considers fundamental questions of how order can emerge, emphasizing the concept of chemical organization (a closed and self-maintaining set of chemicals); and surveys a range of applications, which include computing, systems modeling in biology, and synthetic life. An appendix provides a Python toolkit for implementing ACs.
Download or read book Protein protein Interactions and Networks written by Anna Panchenko and published by Springer Science & Business Media. This book was released on 2010-04-06 with total page 198 pages. Available in PDF, EPUB and Kindle. Book excerpt: The biological interactions of living organisms, and protein-protein interactions in particular, are astonishingly diverse. This comprehensive book provides a broad, thorough and multidisciplinary coverage of its field. It integrates different approaches from bioinformatics, biochemistry, computational analysis and systems biology to offer the reader a comprehensive global view of the diverse data on protein-protein interactions and protein interaction networks.
Download or read book Evolutionary Innovations and Dynamics in Wagner s Model of Genetic Regulatory Networks written by Yifei Wang and published by . This book was released on 2015 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Drosophila Eye Development written by Kevin Moses and published by Springer Science & Business Media. This book was released on 2002-03-12 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt: 1 Kevin Moses It is now 25 years since the study of the development of the compound eye in Drosophila really began with a classic paper (Ready et al. 1976). In 1864, August Weismann published a monograph on the development of Diptera and included some beautiful drawings of the developing imaginal discs (Weismann 1864). One of these is the first description of the third instar eye disc in which Weismann drew a vertical line separating a posterior domain that included a regular pattern of clustered cells from an anterior domain without such a pattern. Weismann suggested that these clusters were the precursors of the adult ommatidia and that the line marks the anterior edge of the eye. In his first suggestion he was absolutely correct - in his second he was wrong. The vertical line shown was not the anterior edge of the eye, but the anterior edge of a moving wave of patterning and cell type specification that 112 years later (1976) Ready, Hansen and Benzer would name the "morphogenetic furrow". While it is too late to hear from August Weismann, it is a particular pleasure to be able to include a chapter in this Volume from the first author of that 1976 paper: Don Ready! These past 25 years have seen an astonishing explosion in the study of the fly eye (see Fig.
Download or read book Quantitative Physiology written by Shangbin Chen and published by Springer Nature. This book was released on 2021-02-09 with total page 246 pages. Available in PDF, EPUB and Kindle. Book excerpt: Stephen Hawking says that the 21st century will be the century of complexity and indeed now systems biology or medicine means dealing with complexity. Both the genome and physiome have emerged in studying complex physiological systems. Computational and mathematical modeling has been regarded as an efficient tool to boost the understanding about living systems in normal or pathophysiological states. Covering applied methodology, basic case studies and complex applications, this volume provides researchers with an overview of modeling and computational studies of physiology (i.e. quantitative physiology), which is becoming an increasingly important branch of systems biology. This book aims to build multi-scale models to investigate functions in living systems and explain how biomolecules, cells, organs, organ systems and organisms carry out the chemical or physical functions. Some of the models addressed are related to gene expression, calcium signalling, neural activity, blood dynamics and bone mechanics. Combining theory and practice, with extensive use of MATLAB, this book is designed to establish a paradigm for quantitative physiology by integrating biology, mathematics, physics and informatics etc. To benefit from this book, the readers are expected to have a background in general physiology and mathematics
Download or read book Progress in Artificial Intelligence written by Luis Antunes and published by Springer Science & Business Media. This book was released on 2011-10-05 with total page 729 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains a selection of higher quality and reviewed papers of the 15th Portuguese Conference on Artificial Intelligence, EPIA 2011, held in Lisbon, Portugal, in October 2011. The 50 revised full papers presented were carefully reviewed and selected from a total of 203 submissions. The papers are organized in topical sections on affective computing, ambient intelligence environments, artificial intelligence methodologies for games, artificial intelligence in transportation systems, artificial life evolutionary algorithms, computational logic with applications, general artificial intelligence, intelligent robotics, knowledge discovery and business intelligence, multi-agent systems: theory and applications, social simulation and modeling, text mining and applications, and doctoral symposium on artificial intelligence.
