Download or read book Predictive Network Modeling And Experimentation In Complex Biological Systems written by Steven Steinway and published by . This book was released on 2015 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Biology is incredibly complex -- at the molecular, cellular, tissue, and population level, there exists a tremendous number of discrete interacting components tightly regulating the processes that sustain life. Biological systems have traditionally been viewed in a reductionist manner often literally (and metaphorically) through a magnifying glass, leading to insight into how the individual parts work. Network theory, on the other hand, can be used to put the pieces together, to understand how complex and emergent behaviors arise from the totality of interactions in complex systems, such as those seen in biology. Network theory is the study of systems of discrete interacting components and provides a framework for understanding complex systems. A network-focused investigation of a complex biological system allows for the understanding of the system's emergent properties, for example its function and dynamics. Network dynamics are of particular interest biologically because biological systems are not static but are constantly changing in response to perturbations and environmental stimuli in space and time. Systems level biological analysis has been aided by the recent explosion of high throughput data. This has led to an abundance of quantitative and qualitative information related to the activation of biological systems, but frequently there is still a paucity of kinetic and temporal information. Discrete dynamic modeling provides a means to create predictive models of biological systems by integrating fragmentary and qualitative interaction information. Using discrete dynamic modeling, a structural (static) network of biological regulatory relationships can be translated into a mathematical model without the use of kinetic parameters. This model can describe the dynamics of a biological system (i.e. how it changes over time), both in normal and in perturbation (e.g. disease) scenarios. In this dissertation we present the application of network theory and discrete dynamic modeling integrated with experimental laboratory analysis to understand biological diseases in three contexts. The first is the construction of a network model of epidermal derived growth factor receptor (EGFR) signaling in cancer. We translate this model into two types of discrete models: a Boolean model and a three-state model. We show how the effects of an EGFR inhibitor (such as the drug gefitinib) can suppress tumor growth, and we model how genomic variants can augment the effect of EGFR inhibition in tumor growth. Importantly, we compare discrete modeling outcomes to an alternative modeling framework, which relies on detailed kinetic information, called ordinary differential equation (ODE) modeling and show that both models achieve similar findings. Our results demonstrate that discrete dynamic model can accurately model biomedical systems and make important predictions about the effect a drug will have on a disease (e.g. tumor growth) in the context of various perturbations. Importantly, discrete dynamic models can be employed in the absence of kinetic parameters, making this modeling approach suitable for the many biological systems in which detailed kinetic information is not available. Second, we construct a network model of epithelial-to-mesenchymal transition (EMT), a developmental process hijacked by cancer cells to leave the primary tumor site, invade surrounding tissue, and establish distant metastases. We demonstrate that the EMT network model recapitulates known dysregulations during the induction of EMT and predicts the activation of the Wnt and Sonic hedgehog (SHH) signaling pathways during this process. We confirm the cross-talk between TGF[beta], Wnt and SHH signaling in vitro in multiple human liver cancer cell lines and tumor samples. Next, we use the EMT network model to systematically explore perturbations that suppress EMT, with the ultimate goal of identifying therapeutic interventions that suppress tumor invasion. We computationally explore close to half a million individual and combination perturbations to the EMT network and identify that only a dozen suppress EMT. We test these interventions experimentally and our findings suggest that many predicted interventions suppress the EMT process. Lastly, we construct a model of the enormous ecological community of bacteria that live in our intestines, collectively called the gut microbiome. This model is used to understand the effect of antibiotic treatment and opportunistic C. difficile infection (a devastating and highly prevalent disease entity) on the native microbiome and predict therapeutic probiotic interventions to suppress C. difficile infection. We integrate this modeling with another type of modeling, genome scale metabolic network reconstructions, to understand metabolic differences between community members and to identify the role of metabolism in the observed microbial interactions. In vitro experimental data validate a key result of my computational model, that Barnesiella intestinihominis can in fact suppress C. difficile growth. This novel result suggests that Barnesiella could potentially be used as a probiotic to suppress C. difficile growth.Taken together, the studies presented in this thesis demonstrate the tremendous capacity of network modeling to elucidate biomedical systems. We build networks, construct mathematical models, study network dynamics, and use network-directed insight to guide experiments in critical biomedical areas. The ultimate goal of this work has been to translate network-directed insight into actionable biomedical findings that lead to improved understanding of human disease, enhanced patient care, and a betterment of the human condition.
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 Boolean Networks as Predictive Models of Emergent Biological Behaviors written by Jordan C. Rozum and published by Cambridge University Press. This book was released on 2024-03-28 with total page 118 pages. Available in PDF, EPUB and Kindle. Book excerpt: Interacting biological systems at all organizational levels display emergent behavior. Modeling these systems is made challenging by the number and variety of biological components and interactions – from molecules in gene regulatory networks to species in ecological networks – and the often-incomplete state of system knowledge, such as the unknown values of kinetic parameters for biochemical reactions. Boolean networks have emerged as a powerful tool for modeling these systems. This Element provides a methodological overview of Boolean network models of biological systems. After a brief introduction, the authors describe the process of building, analyzing, and validating a Boolean model. They then present the use of the model to make predictions about the system's response to perturbations and about how to control its behavior. The Element emphasizes the interplay between structural and dynamical properties of Boolean networks and illustrates them in three case studies from disparate levels of biological organization.
Download or read book Handbook on Biological Networks written by Stefano Boccaletti and published by World Scientific. This book was released on 2010 with total page 465 pages. Available in PDF, EPUB and Kindle. Book excerpt: Networked systems are all around us. The accumulated evidence of systems as complex as a cell cannot be fully understood by studying only their isolated constituents, giving rise to a new area of interest in research OCo the study of complex networks . In a broad sense, biological networks have been one of the most studied networks, and the field has benefited from many important contributions. By understanding and modeling the structure of a biological network, a better perception of its dynamical and functional behavior is to be expected. This unique book compiles the most relevant results and novel insights provided by network theory in the biological sciences, ranging from the structure and dynamics of the brain to cellular and protein networks and to population-level biology. Sample Chapter(s). Chapter 1: Introduction (61 KB). Contents: Networks at the Cellular Level: The Structural Network Properties of Biological Systems (M Brilli & P Li); Dynamics of Multicellular Synthetic Gene Networks (E Ullner et al.); Boolean Networks in Inference and Dynamic Modeling of Biological Systems at the Molecular and Physiological Level (J Thakar & R Albert); Complexity of Boolean Dynamics in Simple Models of Signaling Networks and in Real Genetic Networks (A D az-Guilera & R ulvarez-Buylla); Geometry and Topology of Folding Landscapes (L Bongini & L Casetti); Elastic Network Models for Biomolecular Dynamics: Theory and Application to Membrane Proteins and Viruses (T R Lezon et al.); Metabolic Networks (M C Palumbo et al.); Brain Networks: The Human Brain Network (O Sporns); Brain Network Analysis from High-Resolution EEG Signals (F De Vico Fallani & F Babiloni); An Optimization Approach to the Structure of the Neuronal layout of C elegans (A Arenas et al.); Cultured Neuronal Networks Express Complex Patterns of Activity and Morphological Memory (N Raichman et al.); Synchrony and Precise Timing in Complex Neural Networks (R-M Memmesheimer & M Timme); Networks at the Individual and Population Levels: Ideas for Moving Beyond Structure to Dynamics of Ecological Networks (D B Stouffer et al.); Evolutionary Models for Simple Biosystems (F Bagnoli); Evolution of Cooperation in Adaptive Social Networks (S Van Segbroeck et al.); From Animal Collectives and Complex Networks to Decentralized Motion Control Strategies (A Buscarino et al.); Interplay of Network State and Topology in Epidemic Dynamics (T Gross). Readership: Advanced undergraduates, graduate students and researchers interested in the study of complex networks in a wide range of biological processes and systems."
Download or read book Networks of Networks in Biology written by Narsis A. Kiani and published by Cambridge University Press. This book was released on 2021-04 with total page 215 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduces network inspired approaches for the analysis and integration of large, heterogeneous data sets in the life sciences.
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.
Download or read book Biological Networks written by Francois Kepes and published by World Scientific. This book was released on 2007 with total page 531 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume presents a timely and comprehensive overview of biological networks at all organization levels in the spirit of the complex systems approach. It discusses the transversal issues and fundamental principles as well as the overall structure, dynamics, and modeling of a wide array of biological networks at the molecular, cellular, and population levels. Anchored in both empirical data and a strong theoretical background, the book therefore lends valuable credence to the complex systems approach. Sample Chapter(s). Chapter 1: Scale-Free Networks in Biology (821 KB). Contents: Scale-Free Networks in Biology (E Almaas et al.); Modularity in Biological Networks (R V Sol(r) et al.); Inference of Biological Regulatory Networks: Machine Learning Approaches (F d''Alch(r)-Buc); Transcriptional Networks (F K(r)p s); Protein Interaction Networks (K Tan & T Ideker); Metabolic Networks (D A Fell); Heterogeneous Molecular Networks (V Schnchter); Evolution of Regulatory Networks (A Veron et al.); Complexity in Neuronal Networks (Y Fr(r)gnac et al.); Networks of the Immune System (R E Callard & J Stark); A History of the Study of Ecological Networks (L-F Bersier); Dynamic Network Models of Ecological Diversity, Complexity, and Nonlinear Persistence (R J Williams & N D Martinez); Infection Transmission through Networks (J S Koopman). Readership: Graduate students and industry experts in systems biology and complex systems; biologists; chemists; physicists; mathematicians; computer scientists
Download or read book Network Biology written by WenJun Zhang and published by Nova Science Publishers. This book was released on 2013 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Biological network analysis is a fast moving science. Many core scientific issues; for example, ecological structure, coevolution, coextinction and biodiversity conservation in ecology, cancer development and metabolic regulation in health science, etc., are expected to be addressed by network analysis. Network analysis is becoming the core methodology to treat complex biological systems. With the quick development of this science, more and more papers on biological networks are published. This book includes such theories and methods of network biology as methodology of social network analyses, construction of statistic networks, phylogenetic networks, multi-stable and oscillatory biological networks, creation of real networks with expected degree distribution, forest ecosystem model, etc. Chapters are contributed by 15 scientists from the USA, Canada, New Zealand, China, Sweden, and Spain, in the areas of computational science and life sciences. It will provide researchers with various aspects of the latest advances in network biology. It is a valuable reference for scientists, university teachers and graduate students in biology, health science, ecology, social science, applied mathematics and computational science.
Download or read book Gene Regulatory Networks written by Michael Verdicchio and published by . This book was released on 2013 with total page 203 pages. Available in PDF, EPUB and Kindle. Book excerpt: Biological systems are complex in many dimensions as endless transportation and communication networks all function simultaneously. Our ability to intervene within both healthy and diseased systems is tied directly to our ability to understand and model core functionality. The progress in increasingly accurate and thorough high-throughput measurement technologies has provided a deluge of data from which we may attempt to infer a representation of the true genetic regulatory system. A gene regulatory network model, if accurate enough, may allow us to perform hypothesis testing in the form of computational experiments. Of great importance to modeling accuracy is the acknowledgment of biological contexts within the models -- i.e. recognizing the heterogeneous nature of the true biological system and the data it generates. This marriage of engineering, mathematics and computer science with systems biology creates a cycle of progress between computer simulation and lab experimentation, rapidly translating interventions and treatments for patients from the bench to the bedside. This dissertation will first discuss the landscape for modeling the biological system, explore the identification of targets for intervention in Boolean network models of biological interactions, and explore context specificity both in new graphical depictions of models embodying context-specific genomic regulation and in novel analysis approaches designed to reveal embedded contextual information. Overall, the dissertation will explore a spectrum of biological modeling with a goal towards therapeutic intervention, with both formal and informal notions of biological context, in such a way that will enable future work to have an even greater impact in terms of direct patient benefit on an individualized level.
Download or read book DOE Genomics written by and published by . This book was released on 2005 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Modeling and Simulation of Biological Networks written by American Mathematical Society. Short Course, Modeling and Simulation of Biological Networks and published by American Mathematical Soc.. This book was released on 2007-08-21 with total page 172 pages. Available in PDF, EPUB and Kindle. Book excerpt: It is the task of computational biology to help elucidate the unique characteristics of biological systems. This process has barely begun, and many researchers are testing computational tools that have been used successfully in other fields. Mathematical and statistical network modeling is an important step toward uncovering the organizational principles and dynamic behavior of biological networks. Undoubtedly, new mathematical tools will be needed, however, to meet this challenge. The workhorse of this effort at present comprises the standard tools from applied mathematics, which have proven to be successful for many problems. But new areas of mathematics not traditionally considered applicable are contributing other powerful tools. This volume is intended to introduce this topic to a broad mathematical audience. The aim is to explain some of the biology and the computational and mathematical challenges we are facing. The different chapters provide examples of how these challenges are met, with particular emphasis on nontraditional mathematical approaches. The volume features a broad spectrum of networks across scales, ranging from biochemical networks within a single cell to epidemiological networks encompassing whole cities. Chapter topics include phylogenetics and gene finding using tools from statistics and algebraic geometry, biochemical network inference using tools from computational algebra, control-theoretic approaches to drug delivery using differential equations, and interaction-based modeling and discrete mathematics applied to problems in population dynamics and epidemiology.
Download or read book New Frontiers of Network Analysis in Systems Biology written by Avi Ma'ayan and published by Springer. This book was released on 2012-06-26 with total page 202 pages. Available in PDF, EPUB and Kindle. Book excerpt: The rapidly developing field of systems biology is influencing many aspects of biological research and is expected to transform biomedicine. Some emerging offshoots and specialized branches in systems biology are receiving particular attention and are becoming highly active areas of research. This collection of invited reviews describes some of the latest cutting-edge experimental and computational advances in these emerging sub-fields of systems biology. In particular, this collection focuses on the study of mammalian embryonic stem cells; new technologies involving mass-spectrometry proteomics; single cell measurements; methods for modeling complex stochastic systems; network-based classification algorithms; and the revolutionary emerging field of systems pharmacology.
Download or read book Analysis of Complex Networks written by Matthias Dehmer and published by . This book was released on 2009 with total page 480 pages. Available in PDF, EPUB and Kindle. Book excerpt: Annotation Mathematical problems such as graph theory problems are of increasing importance for the analysis of modelling data in biomedical research such as in systems biology, neuronal network modelling etc. This book follows a new approach of including graph theory from a mathematical perspective with specific applications of graph theory in biomedical and computational sciences. The book is written by renowned experts in the field and offers valuable background information for a wide audience.
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 and Simulation of Biological Networks written by American Mathematical Society. Short Course, Modeling and Simulation of Biological Networks and published by American Mathematical Society(RI). This book was released on 2014-05-10 with total page 160 pages. Available in PDF, EPUB and Kindle. Book excerpt: It is the task of computational biology to help elucidate the unique characteristics of biological systems. This process has barely begun, and many researchers are testing computational tools that have been used successfully in other fields. Mathematical and statistical network modeling is an important step toward uncovering the organizational principles and dynamic behavior of biological networks. Undoubtedly, new mathematical tools will be needed, however, to meet this challenge. The workhorse of this effort at present comprises the standard tools from applied mathematics, which have proven to be successful for many problems. But new areas of mathematics not traditionally considered applicable are contributing other powerful tools. This volume is intended to introduce this topic to a broad mathematical audience. The aim is to explain some of the biology and the computational and mathematical challenges we are facing. The different chapters provide examples of how these challenges are met, with particular emphasis on nontraditional mathematical approaches.The volume features a broad spectrum of networks across scales, ranging from biochemical networks within a single cell to epidemiological networks encompassing whole cities. Chapter topics include phylogenetics and gene finding using tools from statistics and algebraic geometry, biochemical network inference using tools from computational algebra, control-theoretic approaches to drug delivery using differential equations, and interaction-based modeling and discrete mathematics applied to problems in population dynamics and epidemiology.
Download or read book Network Architecture for Prediction of Emergence in Complex Biological Systems written by Gourab Ghosh Roy and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Springer Handbook of Automation written by Shimon Y. Nof and published by Springer Science & Business Media. This book was released on 2009-07-16 with total page 1841 pages. Available in PDF, EPUB and Kindle. Book excerpt: This handbook incorporates new developments in automation. It also presents a widespread and well-structured conglomeration of new emerging application areas, such as medical systems and health, transportation, security and maintenance, service, construction and retail as well as production or logistics. The handbook is not only an ideal resource for automation experts but also for people new to this expanding field.
