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Genomescale metabolic model of Helicobacter pylori 26695
 J Bacteriol
, 2002
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These include: This article cites 62 articles, 29 of which can be accessed free at:
Energy balance for analysis of complex metabolic networks
 Biophys. J
, 2002
"... ABSTRACT Predicting behavior of largescale biochemical networks represents one of the greatest challenges of bioinformatics and computational biology. Computational tools for predicting fluxes in biochemical networks are applied in the fields of integrated and systems biology, bioinformatics, and g ..."
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ABSTRACT Predicting behavior of largescale biochemical networks represents one of the greatest challenges of bioinformatics and computational biology. Computational tools for predicting fluxes in biochemical networks are applied in the fields of integrated and systems biology, bioinformatics, and genomics, and to aid in drug discovery and identification of potential drug targets. Approaches, such as flux balance analysis (FBA), that account for the known stoichiometry of the reaction network while avoiding implementation of detailed reaction kinetics are promising tools for the analysis of large complex networks. Here we introduce energy balance analysis (EBA)—the theory and methodology for enforcing the laws of thermodynamics in such simulations—making the results more physically realistic and revealing greater insight into the regulatory and control mechanisms operating in complex largescale systems. We show that EBA eliminates thermodynamically infeasible results associated with FBA. INTRODUCTION AND BACKGROUND Conservation principles impose constraints on the fluxes and chemical potentials associated with biochemical network reactions that are analogous to Kirchoff’s current and voltage laws for electrical networks (Balabanian and Bickart,
Metabolic pathways in the postgenome era
 Trends in Biochem. Sci
, 2003
"... Metabolic pathways are a central paradigm in biology. Historically, they have been defined on the basis of their stepbystep discovery. However, the genomescale metabolic networks now being reconstructed from annotation of genome sequences demand new networkbased definitions of pathways to facili ..."
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Metabolic pathways are a central paradigm in biology. Historically, they have been defined on the basis of their stepbystep discovery. However, the genomescale metabolic networks now being reconstructed from annotation of genome sequences demand new networkbased definitions of pathways to facilitate analysis of their capabilities and functions, such as metabolic versatility and robustness, and optimal growth rates. This demand has led to the development of a new mathematically based analysis of complex, metabolic networks that enumerates all their unique pathways that take into account all requirements for cofactors and byproducts. Applications include the design of engineered biological systems, the generation of testable hypotheses regarding network structure and function, and the elucidation of properties that can not be described by simple descriptions of individual components (such as product yield, network robustness, correlated reactions and predictions of minimal media). Recently, these properties have also been studied in genomescale networks. Thus, networkbased pathways are emerging as an important paradigm for analysis of biological systems. The highthroughput experimental technologies that have rapidly developed within genomic science allow us to obtain comprehensive data about the molecular makeup of cells, thus enabling us to reconstruct largescale (even genomescale) reaction networks To date, traditional metabolic pathways [4] have served as conceptual frameworks for research and teaching. These pathways provide an important means of effective Most of these reactions have been grouped into 'traditional pathways' (e.g. glycolysis) that do not account for cofactors and byproducts in a way that lends itself to a mathematical description. With sequenced and annotated genomes, models can be made that account for many metabolic reactions in an organism. (c) Subsequently, networkbased, mathematically defined pathways can be analyzed that account for a complete network (note that black and gray arrows correspond to active and inactive reactions, respectively).
Parallel Outofcore Algorithm for GenomeScale Enumeration of Metabolic Systemic Pathways
 Proc. First IEEE Workshop on High Performance Computat. Biol. (HiCOMB2002
, 2002
"... Systemic pathwaysoriented approaches to analysis of metabolic networks are effective for small networks but are computationally infeasible for genome scale networks. Current computational approaches to this analysis are based on the mathematical principles of convex analysis. The enumeration of a c ..."
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Systemic pathwaysoriented approaches to analysis of metabolic networks are effective for small networks but are computationally infeasible for genome scale networks. Current computational approaches to this analysis are based on the mathematical principles of convex analysis. The enumeration of a complete set of "systemically independent" metabolic pathways is at the core of these approaches and it is computationally the most demanding component. An efficient parallel outof core algorithm for generating a complete set of systemically independent metabolic pathways, termed "extreme pathways", is presented. These pathways represent the edges of a highdimensional convex cone and can be used to derive any admissible steadystate flux distribution (or phenotype) for a specified metabolic genotype. The algorithm can be used for computing "elementary flux modes" that are different but closely related to extreme pathways. The algorithm combines a bitmap data representation, search space reduction, and outofcore implementation to improve CPUtime and memory requirements by several orders of magnitude. Augmented with a parallel implementation, it provides extremely scalable performance. No previous parallel and/or outofcore algorithms for the enumeration of systemically defined metabolic pathways are known.
Bayesianbased selection of metabolic objective functions
"... doi:10.1093/bioinformatics/btl619 ..."
Recent advances in ecological stoichiometry: Insights for population and community ecology
 OIKOS 109:29–39
, 2005
"... Conventional theories of population and community dynamics are based on a single currency such as number of individuals, biomass, carbon or energy. However, organisms are constructed of multiple elements and often require them (in particular carbon, phosphorus and nitrogen) in different ratios than ..."
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Conventional theories of population and community dynamics are based on a single currency such as number of individuals, biomass, carbon or energy. However, organisms are constructed of multiple elements and often require them (in particular carbon, phosphorus and nitrogen) in different ratios than provided by their resources; this mismatch may constrain the net transfer of energy and elements through trophic levels. Ecological stoichiometry, the study of the balance of elements in ecological processes, offers a framework for exploring ecological effects of such constraints. We review recent theoretical and empirical studies that have considered how stoichiometry may affect population and community dynamics. These studies show that stoichiometric constraints can affect several properties of populations (e.g. stability, oscillations, consumer extinction) and communities (e.g. coexistence of competitors, competitive interactions between different guilds). We highlight gaps in general knowledge and focus on areas of population and community ecology where incorporation of stoichiometric constraints may be particularly fruitful, such as studies of demographic bottlenecks, spatial processes, and multispecies interactions.
Genomescale computational approaches to memoryintensive applications in systems biology
 In Proceedings, Supercomputing
, 2005
"... Graphtheoretical approaches to biological network analysis have proven to be effective for small networks but are computationally infeasible for comprehensive genomescale systemslevel elucidation of these networks. The difficulty lies in the NPhard nature of many global systems biology problems ..."
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Graphtheoretical approaches to biological network analysis have proven to be effective for small networks but are computationally infeasible for comprehensive genomescale systemslevel elucidation of these networks. The difficulty lies in the NPhard nature of many global systems biology problems that, in practice, translates to exponential (or worse) run times for finding exact optimal solutions. Moreover, these problems, especially those of an enumerative flavor, are often memoryintensive and must share very large sets of data effectively across many processors. For example, the enumeration of maximal cliques – a core component in gene expression networks analysis, cis regulatory motif finding, and the study of quantitative trait loci for highthroughput molecular phenotypes – can result in as many as 3 n/3 maximal cliques for a graph with n vertices. Memory requirements to store those cliques reach terabyte scales even on modestsized genomes. Emerging hardware architectures with ultralarge globally addressable memory such as the SGI Altix and Cray X1 seem to be well suited for addressing these types of dataintensive problems in systems biology. This paper presents a novel framework that provides exact, parallel and scalable solutions to various graphtheoretical approaches to genomescale elucidation of biological networks. This framework takes advantage of these largememory architectures by creating globally addressable bitmap memory indices with potentially high compression rates, fast bitwiselogical operations, and
B.M.: Experimental and mathematical approaches to modeling plant metabolic networks
 Phytochemistry
, 2007
"... This article is dedicated to the memory of Reinhart Heinrich, one of the founding fathers of metabolic control theory and a pioneer of systems biology. Abstract To support their sessile and autotrophic lifestyle higher plants have evolved elaborate networks of metabolic pathways. Dynamic changes in ..."
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This article is dedicated to the memory of Reinhart Heinrich, one of the founding fathers of metabolic control theory and a pioneer of systems biology. Abstract To support their sessile and autotrophic lifestyle higher plants have evolved elaborate networks of metabolic pathways. Dynamic changes in these metabolic networks are among the developmental forces underlying the functional differentiation of organs, tissues and specialized cell types. They are also important in the various interactions of a plant with its environment. Further complexity is added by the extensive compartmentation of the various interconnected metabolic pathways in plants. Thus, although being used widely for assessing the control of metabolic flux in microbes, mathematical modeling approaches that require steadystate approximations are of limited utility for understanding complex plant metabolic networks. However, considerable progress has been made when manageable metabolic subsystems were studied. In this article, we will explain in general terms and using simple examples the concepts underlying stoichiometric modeling (metabolic flux analysis and metabolic pathway analysis) and kinetic approaches to modeling (including metabolic control analysis as a special case). Selected studies demonstrating the prospects of these approaches, or combinations of them, for understanding the control of flux through particular plant pathways are discussed. We argue that iterative cycles of (dry) mathematical modeling and (wet) laboratory testing will become increasingly important for simulating the distribution of flux in plant metabolic networks and deriving rational experimental designs for metabolic engineering efforts.
Metabolic Engineering in the omics Era: Elucidating and Modulating Regulatory Networks
 Microbiology and Molecular Biology Reviews
, 2005
"... The importance of regulatory control in metabolic processes is widely acknowledged, and several enquiries (both local and global) are being made in understanding regulation at various levels of the metabolic hierarchy. The wealth of biological information has enabled identifying the individual compo ..."
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The importance of regulatory control in metabolic processes is widely acknowledged, and several enquiries (both local and global) are being made in understanding regulation at various levels of the metabolic hierarchy. The wealth of biological information has enabled identifying the individual components (genes, proteins, and metabolites) of a biological system, and we are now in a position to understand the interactions between these components. Since phenotype is the net result of these interactions, it is immensely important to elucidate them not only for an integrated understanding of physiology, but also for practical applications of using biological systems as cell factories. We present some of the recent "omics" approaches that have expanded our understanding of regulation at the gene, protein, and metabolite level, followed by analysis of the impact of this progress on the advancement of metabolic engineering. Although this review is by no means exhaustive, we attempt to convey our ideology that combining global information from various levels of metabolic hierarchy is absolutely essential in understanding and subsequently predicting the relationship between changes in gene expression and the resulting phenotype. The ultimate aim of this review is to provide metabolic engineers with an overview of recent advances in complementary aspects of regulation at the gene, protein, and metabolite level and those involved in fundamental research with potential hurdles in the path to implementing their discoveries in practical applications.
Metabolic Network Model of a Human Oral Pathogen � ‡
, 2008
"... This article cites 97 articles, 39 of which can be accessed free ..."
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This article cites 97 articles, 39 of which can be accessed free