Download or read book Systems Biology Informatics for the Development and Use of Genome scale Metabolic Models written by Neil Swainston and published by . This book was released on 2012 with total page 175 pages. Available in PDF, EPUB and Kindle. Book excerpt: Systems biology attempts to understand biological systems through the generation of predictive models that allow the behaviour of the system to be simulated in silico. Metabolic systems biology has in recent years focused upon the reconstruction and constraint-based analysis of genome-scale metabolic networks, which provide computational and mathematical representations of the known metabolic capabilities of a given organism. This thesis initially concerns itself with the development of such metabolic networks, first considering the community-driven development of consensus networks of the metabolic functions of Saccharomyces cerevisiae. This is followed by a consideration of automated approaches to network reconstruction that can be applied to facilitate what has, until recently, been an arduous manual process. The use of such large-scale networks in the generation of dynamic kinetic models is then considered. The development of such models is dependent upon the availability of experimentally determined parameters, from omics approaches such as transcriptomics, proteomics and metabolomics, and from kinetic assays. A discussion of the challenges faced with developing informatics infrastructure to support the acquisition, analysis and dissemination of quantitative proteomics and enzyme kinetics data follows, along with the introduction of novel software approaches to address these issues. The requirement for integrating experimental data with kinetic models is considered, along with approaches to construct, parameterise and simulate kinetic models from the network reconstructions and experimental data discussed previously. Finally, future requirements for metabolic systems biology informatics are considered, in the context of experimental data management, modelling infrastructure, and data integration required to bridge the gap between experimental and modelling approaches.
Download or read book Metabolic Pathway Engineering written by Jean F. Challacombe and published by CRC Press. This book was released on 2021-07-14 with total page 116 pages. Available in PDF, EPUB and Kindle. Book excerpt: Metabolic systems engineering combines the tools and approaches of systems biology, synthetic biology, and evolutionary engineering. This book reviews studies on metabolism, from the earliest work of Lavoisier and Buchner to current cutting-edge research in metabolic systems engineering. This technology has been used in bioengineering applications to create high-performing microbes and plants that produce important chemicals, pharmaceuticals, crops, and other natural products. Current applications include optimizing metabolic pathways to enhance degradation of biomass for biofuel production and accelerated processing of environmental waste products and contaminants. The book includes examples to illustrate the applications of this technology in the optimization of metabolic pathways to create robust industrial strains as well as in the engineering of biological processes involving health and diseases of humans, animals, and plants. Written by a seasoned computational biologist with many years of experience in genomics, bioinformatics, and systems biology, this book will appeal to anyone interested in metabolic systems analysis and metabolic pathway engineering.
Download or read book Current Challenges in Modeling Cellular Metabolism written by Daniel Machado and published by Frontiers Media SA. This book was released on 2016-01-21 with total page 117 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mathematical and computational models play an essential role in understanding the cellular metabolism. They are used as platforms to integrate current knowledge on a biological system and to systematically test and predict the effect of manipulations to such systems. The recent advances in genome sequencing techniques have facilitated the reconstruction of genome-scale metabolic networks for a wide variety of organisms from microbes to human cells. These models have been successfully used in multiple biotechnological applications. Despite these advancements, modeling cellular metabolism still presents many challenges. The aim of this Research Topic is not only to expose and consolidate the state-of-the-art in metabolic modeling approaches, but also to push this frontier beyond the current edge through the introduction of innovative solutions. The articles presented in this e-book address some of the main challenges in the field, including the integration of different modeling formalisms, the integration of heterogeneous data sources into metabolic models, explicit representation of other biological processes during phenotype simulation, and standardization efforts in the representation of metabolic models and simulation results.
Download or read book Metabolome Analyses written by Seetharaman Vaidyanathan and published by Springer Science & Business Media. This book was released on 2006-03-20 with total page 396 pages. Available in PDF, EPUB and Kindle. Book excerpt: Metabolome analysis is now recognized as a crucial component of functional genomic and systems biology investigations. Innovative approaches to the study of metabolic regulation in microbial, plant and animal systems are increasingly facilitating the emergence of systems approaches in biology. This book highlights analytical and bioinformatics strategies now available for investigating metabolic networks in microbial, plant and animal systems. The contributing authors are world leaders in this field and they present an unambiguous case for pursuing metabolome analysis as a means to attain a systems level understanding of complex biological systems.
Download or read book Foundations of Systems Biology written by Masao Nagasaki and published by Springer Science & Business Media. This book was released on 2009-04-21 with total page 166 pages. Available in PDF, EPUB and Kindle. Book excerpt: Today, as hundreds of genomes have been sequenced and thousands of proteins and more than ten thousand metabolites have been identi?ed, navigating safely through this wealth of information without getting completely lost has become crucial for research in, and teaching of, molecular biology. Consequently, a considerable number of tools have been developed and put on the market in the last two decades that describe the multitude of potential/putative interactions between genes, proteins, metabolites, and other biologically relevant compounds in terms of metabolic, genetic, signaling, and other networks, their aim being to support all sorts of explorations through bio-data bases currently called Systems Biology. As a result, navigating safely through this wealth of information-processing tools has become equally crucial for successful work in molecular biology. To help perform such navigation tasks successfully, this book starts by providing an extremely useful overview of existing tools for ?nding (or designing) and inv- tigating metabolic, genetic, signaling, and other network databases, addressing also user-relevant practical questions like • Is the database viewable through a web browser? • Is there a licensing fee? • What is the data type (metabolic, gene regulatory, signaling, etc. )? • Is the database developed/maintained by a curator or a computer? • Is there any software for editing pathways? • Is it possible to simulate the pathway? It then goes on to introduce a speci?c such tool, that is, the fabulous “Cell - lustrator 3. 0” tool developed by the authors.
Download or read book Systems and Synthetic Metabolic Engineering written by Yanfeng Liu and published by Academic Press. This book was released on 2020-07-10 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt: Systems and Synthetic Metabolic Engineering provides an overview of the development of metabolic engineering within medicine that is fueled by systems and synthetic biology. These newly developed, successful strategies of metabolic engineering guide the audience on how to propose and test proper strategies for metabolic engineering research. In addition to introductory, regulatory and challenges in the field, the book also covers dynamic control and autonomous regulation to control cell metabolism, along with computational modeling and industrial applications. The book is written by leaders in the field, making it ideal for synthetic biologists, researchers, students and anyone working in this area. - Discusses the current progress of metabolic engineering, focusing on systems biology and synthetic biology - Covers introductory, regulatory, strategies, production and challenges in the field - Written technically for synthetic biologists, researchers, students, industrialists, policymakers and stakeholders
Download or read book Bridging the Genomic Gaps written by and published by . This book was released on 2018 with total page 113 pages. Available in PDF, EPUB and Kindle. Book excerpt: The advent of next-generation DNA sequencing and the acceleration of computational resources have significantly impacted the speed at which genetic information from microbes and the environments they occupy is obtained and processed. However, these tools have also revealed the limitation of our knowledge base. Sequencing depth and volume are uncovering gene products with little-to-no shared sequence similarity to current collections and databases, thus impeding the ability of homology-based approaches to characterize all sequenced genetic material and downstream analyses describing metabolic capabilities and functional diversity. In silico genome-scale metabolic models are increasingly supplementing genomic and metagenomic studies. These metabolic models enable exploration of the metabolism of an organism within a systems biology perspective. As a reconstruction of the complex metabolic network, models contain information on the genes, enzymes, biochemical reactions, and metabolites of an organism. Metabolic models are typically used with constraint-based linear programming methods to predict cellular phenotypic properties in various growth conditions. Furthermore, metabolic models are reconciled with experimentation to improve the model’s predictive accuracy and to increase our knowledge base of the organism, providing opportunities to use quantitative methods to analyze the bacterial cell. This thesis project aims to exploit genome-scale metabolic models to extend the traditional bioinformatics workflow to provide more accurate descriptions of bacteria, to quantitatively characterize the metabolic landscape of bacteria, and to produce a development environment where systems biology questions are explored and tested. With PMAnalyzer and PyFBA, these computational tools provide the infrastructure to facilitate the aims of this project. PMAnalyzer quickly and automatically calculates bacterial growth properties (e.g, growth rate and yield) from temporal absorbance data measuring cellular accumulation. PyFBA supplies a programmatic environment to explore and use genome-scale metabolic models built from genomic annotations. The use of phenotypic observations and metabolic predictions will provide a new context to discuss genomic-based studies. This project involves studies describing taxonomically-diverse bacteria isolated from the Southern California kelp forest environment.
Download or read book Computational Biology and Genome Informatics written by Jason T. L. Wang and published by World Scientific. This book was released on 2003 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains articles written by experts on a wide range oftopics that are associated with the analysis and management ofbiological information at the molecular level. It contains chapters onRNA and protein structure analysis, DNA computing, sequence mapping, genome comparison, gene expression data mining, metabolic networkmodeling, and phyloinformatics
Download or read book Computational Biology and Machine Learning for Metabolic Engineering and Synthetic Biology written by Kumar Selvarajoo and published by Springer Nature. This book was released on 2022-10-13 with total page 457 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume provides protocols for computational, statistical, and machine learning methods that are mainly applied to the study of metabolic engineering, synthetic biology, and disease applications. These techniques support the latest progress in cross-disciplinary research that integrates the different scales of biological complexity. The topics covered in this book are geared toward researchers with a background in engineering, computational analytical, and modeling experience and cover a broad range of topics in computational and machine learning approaches. 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. Comprehensive and practical, Computational Biology and Machine Learning for Metabolic Engineering and Synthetic Biology is a valuable resource for any researcher or scientist who wants to learn more about the latest computational methods and how they are applied toward the understanding and prediction of complex biology.
Download or read book The OME Framework for Genome scale Systems Biology written by and published by . This book was released on 2014 with total page 23 pages. Available in PDF, EPUB and Kindle. Book excerpt: The life sciences are undergoing continuous and accelerating integration with computational and engineering sciences. The biology that many in the field have been trained on may be hardly recognizable in ten to twenty years. One of the major drivers for this transformation is the blistering pace of advancements in DNA sequencing and synthesis. These advances have resulted in unprecedented amounts of new data, information, and knowledge. Many software tools have been developed to deal with aspects of this transformation and each is sorely needed [1-3]. However, few of these tools have been forced to deal with the full complexity of genome-scale models along with high throughput genome- scale data. This particular situation represents a unique challenge, as it is simultaneously necessary to deal with the vast breadth of genome-scale models and the dizzying depth of high-throughput datasets. It has been observed time and again that as the pace of data generation continues to accelerate, the pace of analysis significantly lags behind [4]. It is also evident that, given the plethora of databases and software efforts [5-12], it is still a significant challenge to work with genome-scale metabolic models, let alone next-generation whole cell models [13-15]. We work at the forefront of model creation and systems scale data generation [16-18]. The OME Framework was borne out of a practical need to enable genome-scale modeling and data analysis under a unified framework to drive the next generation of genome-scale biological models. Here we present the OME Framework. It exists as a set of Python classes. However, we want to emphasize the importance of the underlying design as an addition to the discussions on specifications of a digital cell. A great deal of work and valuable progress has been made by a number of communities [13, 19-24] towards interchange formats and implementations designed to achieve similar goals. While many software tools exist for handling genome-scale metabolic models or for genome-scale data analysis, no implementations exist that explicitly handle data and models concurrently. The OME Framework structures data in a connected loop with models and the components those models are composed of. This results in the first full, practical implementation of a framework that can enable genome-scale design-build-test. Over the coming years many more software packages will be developed and tools will necessarily change. However, we hope that the underlying designs shared here can help to inform the design of future software.
Download or read book Metabolomics written by Jens Nielsen and published by Springer Science & Business Media. This book was released on 2007-09-19 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt: Giving a fresh, substantial and in-depth overview of the topic, this book brings together the latest results in the field of metabolomics. It comprehensively presents the current state of the metabolomics field by underscoring experimental methods, analysis techniques, standardization practices, and advances in specific model systems. As a result, it helps to significantly broaden our perspective on the principles and strategies underpinning this emerging field.
Download or read book Frontiers in Computational and Systems Biology written by Jianfeng Feng and published by Springer. This book was released on 2010-06-23 with total page 24 pages. Available in PDF, EPUB and Kindle. Book excerpt: Biological and biomedical studies have entered a new era over the past two decades thanks to the wide use of mathematical models and computational approaches. A booming of computational biology, which sheerly was a theoretician’s fantasy twenty years ago, has become a reality. Obsession with computational biology and theoretical approaches is evidenced in articles hailing the arrival of what are va- ously called quantitative biology, bioinformatics, theoretical biology, and systems biology. New technologies and data resources in genetics, such as the International HapMap project, enable large-scale studies, such as genome-wide association st- ies, which could potentially identify most common genetic variants as well as rare variants of the human DNA that may alter individual’s susceptibility to disease and the response to medical treatment. Meanwhile the multi-electrode recording from behaving animals makes it feasible to control the animal mental activity, which could potentially lead to the development of useful brain–machine interfaces. - bracing the sheer volume of genetic, genomic, and other type of data, an essential approach is, ?rst of all, to avoid drowning the true signal in the data. It has been witnessed that theoretical approach to biology has emerged as a powerful and st- ulating research paradigm in biological studies, which in turn leads to a new - search paradigm in mathematics, physics, and computer science and moves forward with the interplays among experimental studies and outcomes, simulation studies, and theoretical investigations.
Download or read book Machine Learning and Systems Biology in Genomics and Health written by Shailza Singh and published by Springer Nature. This book was released on 2022-02-04 with total page 239 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses the application of machine learning in genomics. Machine Learning offers ample opportunities for Big Data to be assimilated and comprehended effectively using different frameworks. Stratification, diagnosis, classification and survival predictions encompass the different health care regimes representing unique challenges for data pre-processing, model training, refinement of the systems with clinical implications. The book discusses different models for in-depth analysis of different conditions. Machine Learning techniques have revolutionized genomic analysis. Different chapters of the book describe the role of Artificial Intelligence in clinical and genomic diagnostics. It discusses how systems biology is exploited in identifying the genetic markers for drug discovery and disease identification. Myriad number of diseases whether be infectious, metabolic, cancer can be dealt in effectively which combines the different omics data for precision medicine. Major breakthroughs in the field would help reflect more new innovations which are at their pinnacle stage. This book is useful for researchers in the fields of genomics, genetics, computational biology and bioinformatics.
Download or read book Metabolic Engineering written by Sang Yup Lee and published by John Wiley & Sons. This book was released on 2021-06-02 with total page 1075 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn more about foundational and advanced topics in metabolic engineering in this comprehensive resource edited by leaders in the field Metabolic Engineering: Concepts and Applications delivers a one-stop resource for readers seeking a complete description of the concepts, models, and applications of metabolic engineering. This guide offers practical insights into the metabolic engineering of major cell lines, including E. Coli, Bacillus and Yarrowia Lipolytica, and organisms, including human, animal, and plant). The distinguished editors also offer readers resources on microbiome engineering and the use of metabolic engineering in bioremediation. Written in two parts, Metabolic Engineering begins with the essential models and strategies of the field, like Flux Balance Analysis, Quantitative Flux Analysis, and Proteome Constrained Models. It also provides an overview of topics like Pathway Design, Metabolomics, and Genome Editing of Bacteria and Eukarya. The second part contains insightful descriptions of the practical applications of metabolic engineering, including specific examples that shed light on the topics within. In addition to subjects like the metabolic engineering of animals, humans, and plants, you’ll learn more about: Metabolic engineering concepts and a historical perspective on their development The different modes of analysis, including flux balance analysis and quantitative flux analysis An illuminating and complete discussion of the thermodynamics of metabolic pathways The Genome architecture of E. coli, as well as genome editing of both bacteria and eukarya An in-depth treatment of the application of metabolic engineering techniques to organisms including corynebacterial, bacillus, and pseudomonas, and more Perfect for students of biotechnology, bioengineers, and biotechnologists, Metabolic Engineering: Concepts and Applications also has a place on the bookshelves of research institutes, biotechnological institutes and industry labs, and university libraries. It's comprehensive treatment of all relevant metabolic engineering concepts, models, and applications will be of use to practicing biotechnologists and bioengineers who wish to solidify their understanding of the field.
Download or read book Computational Systems Biology written by Hong-Wu Ma and published by Elsevier Inc. Chapters. This book was released on 2013-11-26 with total page 35 pages. Available in PDF, EPUB and Kindle. Book excerpt: Understanding the complex interactions among cellular components (genes, proteins and metabolites) at a network level is a key issue in systems biology. In this chapter, we give an overview of metabolic network reconstruction from genome information and its structural analysis. First, two approaches for genome scale metabolic network reconstruction: high throughput reconstruction and high quality reconstruction, are discussed. Then the various means for mathematical representation of metabolic networks are explained, with particular emphasis on the problem arising from currency metabolites. Several topological features of metabolic network such as the power law connection degree distribution and the “bow-tie” global connectivity structure are explained in detail. In the last section, we discuss the different types of methods for network decomposition which can be used to identify somehow structurally and functionally independent modules in a complex network. This allows us to understand the functional organization of metabolic network from a modular perspective.
Download or read book Systems Biology written by Bernhard Palsson and published by Cambridge University Press. This book was released on 2015-01-26 with total page 551 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first comprehensive single-authored textbook on genome-scale models and the bottom-up approach to systems biology.
