255 research outputs found

    Organising metabolic networks: cycles in flux distributions

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    Metabolic networks are among the most widely studied biological systems. The topology and interconnections of metabolic reactions have been well described for many species, but are not sufficient to understand how their activity is regulated in living organisms. The principles directing the dynamic organisation of reaction fluxes remain poorly understood. Cyclic structures are thought to play a central role in the homeostasis of biological systems and in their resilience to a changing environment. In this work, we investigate the role of fluxes of matter cycling in metabolic networks. First, we introduce a methodology for the computation of cyclic and acyclic fluxes in metabolic networks, adapted from an algorithm initially developed to study cyclic fluxes in trophic networks. Subsequently, we apply this methodology to the analysis of three metabolic systems, including the central metabolism of wild type and a deletion mutant of Escherichia coli, erythrocyte metabolism and the central metabolism of the bacterium Methylobacterium extorquens. The role of cycles in driving and maintaining the performance of metabolic functions upon perturbations is unveiled through these examples. This methodology may be used to further investigate the role of cycles in living organisms, their pro-activity and organisational invariance, leading to a better understanding of biological entailment and information processing

    Rapid algorithm for identifying backbones in the two-dimensional percolation model

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    We present a rapid algorithm for identifying the current-carrying backbone in the percolation model. It applies to general two-dimensional graphs with open boundary conditions. Complemented by the modified Hoshen-Kopelman cluster labeling algorithm, our algorithm identifies dangling parts using their local properties. For planar graphs, it finds the backbone almost four times as fast as Tarjan's depth-first-search algorithm, and uses the memory of the same size as the modified Hoshen-Kopelman algorithm. Comparison with other algorithms for backbone identification is addressed.Comment: 5 pages with 5 eps figures. RevTeX 3.1. Clarify the origin of the hull-generating algorith

    Truly On-The-Fly LTL Model Checking

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    We propose a novel algorithm for automata-based LTL model checking that interleaves the construction of the generalized B\"{u}chi automaton for the negation of the formula and the emptiness check. Our algorithm first converts the LTL formula into a linear weak alternating automaton; configurations of the alternating automaton correspond to the locations of a generalized B\"{u}chi automaton, and a variant of Tarjan's algorithm is used to decide the existence of an accepting run of the product of the transition system and the automaton. Because we avoid an explicit construction of the B\"{u}chi automaton, our approach can yield significant improvements in runtime and memory, for large LTL formulas. The algorithm has been implemented within the SPIN model checker, and we present experimental results for some benchmark examples

    A fast and simple algorithm for the maximum flow problem

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    Includes bibliographical references (p. 31-33)

    Computational investigations of maximum flow algorithms

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    "April 1995."Includes bibliographical references (p. 55-57).by Ravindra K. Ahuja ... [et al.

    Alternative methods for representing the inverse of linear programming basis matrices

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    Methods for representing the inverse of Linear Programming (LP) basis matrices are closely related to techniques for solving a system of sparse unsymmetric linear equations by direct methods. It is now well accepted that for these problems the static process of reordering the matrix in the lower block triangular (LBT) form constitutes the initial step. We introduce a combined static and dynamic factorisation of a basis matrix and derive its inverse which we call the partial elimination form of the inverse (PEFI). This factorization takes advantage of the LBT structure and produces a sparser representation of the inverse than the elimination form of the inverse (EFI). In this we make use of the original columns (of the constraint matrix) which are in the basis. To represent the factored inverse it is, however, necessary to introduce special data structures which are used in the forward and the backward transformations (the two major algorithmic steps) of the simplex method. These correspond to solving a system of equations and solving a system of equations with the transposed matrix respectively. In this paper we compare the nonzero build up of PEFI with that of EFI. We have also investigated alternative methods for updating the basis inverse in the PEFI representation. The results of our experimental investigation are presented in this pape
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