Minimal cut sets in a metabolic network are elementary modes in a dual network

Motivation: Elementary modes (EMs) and minimal cut sets (MCSs) provide important techniques for metabolic network modeling. Whereas EMs describe minimal subnetworks that can function in steady state, MCSs are sets of reactions whose removal will disable certain network functions. Effective algorithms were developed for EM computation while calculation of MCSs is typically addressed by indirect methods requiring the computation of EMs as initial step. Results: In this contribution, we provide a method that determines MCSs directly without calculating the EMs. We introduce a duality framework for metabolic networks where the enumeration of MCSs in the original network is reduced to identifying the EMs in a dual network. As a further extension, we propose a generalization of MCSs in metabolic networks by allowing the combination of inhomogeneous constraints on reaction rates. This framework provides a promising tool to open the concept of EMs and MCSs to a wider class of applications. Contact: [email protected]; [email protected] Supplementary information: Supplementary data are available at Bioinformatics onlin

Computing knock out strategies in metabolic networks

Given a metabolic network in terms of its metabolites and reactions, our goal is to efficiently compute the minimal knock out sets of reactions required to block a given behaviour. We describe an algorithm which improves the computation of these knock out sets when the elementary modes (minimal functional subsystems) of the network are given. We also describe an algorithm which computes both the knock out sets and the elementary modes containing the blocked reactions directly from the description of the network and whose worst-case computational complexity is better than the algorithms currently in use for these problems. Computational results are included.Comment: 12 page

Graph problems arising from parameter identification of discrete dynamical systems

This paper focuses on combinatorial feasibility and optimization problems that arise in the context of parameter identification of discrete dynamical systems. Given a candidate parametric model for a physical system and a set of experimental observations, the objective of parameter identification is to provide estimates of the parameter values for which the model can reproduce the experiments. To this end, we define a finite graph corresponding to the model, to each arc of which a set of parameters is associated. Paths in this graph are regarded as feasible only if the sets of parameters corresponding to the arcs of the path have nonempty intersection. We study feasibility and optimization problems on such feasible paths, focusing on computational complexity. We show that, under certain restrictions on the sets of parameters, some of the problems become tractable, whereas others are NP-hard. In a similar vein, we define and study some graph problems for experimental design, whose goal is to support the scientist in optimally designing new experiment

Reaction-controlled diffusion

The dynamics of a coupled two-component nonequilibrium system is examined by means of continuum field theory representing the corresponding master equation. Particles of species A may perform hopping processes only when particles of different type B are present in their environment. Species B is subject to diffusion-limited reactions. If the density of B particles attains a finite asymptotic value (active state), the A species displays normal diffusion. On the other hand, if the B density decays algebraically ~t^{-a} at long times (inactive state), the effective attractive A-B interaction is weakened. The combination of B decay and activated A hopping processes gives rise to anomalous diffusion, with mean-square displacement ~ t^{1-a} for a < 1. Such algebraic subdiffusive behavior ensues for n-th order B annihilation reactions (n B -> 0) with n >=3, and n = 2 for d < 2. The mean-square displacement of the A particles grows only logarithmically with time in the case of B pair annihilation (n = 2) and d >= 2 dimensions. For radioactive B decay (n = 1), the A particles remain localized. If the A particles may hop spontaneously as well, or if additional random forces are present, the A-B coupling becomes irrelevant, and conventional diffusion is recovered in the long-time limit.Comment: 7 pages, revtex, no figures; latest revised versio

A Logical Model Provides Insights into T Cell Receptor Signaling

Cellular decisions are determined by complex molecular interaction networks. Large-scale signaling networks are currently being reconstructed, but the kinetic parameters and quantitative data that would allow for dynamic modeling are still scarce. Therefore, computational studies based upon the structure of these networks are of great interest. Here, a methodology relying on a logical formalism is applied to the functional analysis of the complex signaling network governing the activation of T cells via the T cell receptor, the CD4/CD8 co-receptors, and the accessory signaling receptor CD28. Our large-scale Boolean model, which comprises 94 nodes and 123 interactions and is based upon well-established qualitative knowledge from primary T cells, reveals important structural features (e.g., feedback loops and network-wide dependencies) and recapitulates the global behavior of this network for an array of published data on T cell activation in wild-type and knock-out conditions. More importantly, the model predicted unexpected signaling events after antibody-mediated perturbation of CD28 and after genetic knockout of the kinase Fyn that were subsequently experimentally validated. Finally, we show that the logical model reveals key elements and potential failure modes in network functioning and provides candidates for missing links. In summary, our large-scale logical model for T cell activation proved to be a promising in silico tool, and it inspires immunologists to ask new questions. We think that it holds valuable potential in foreseeing the effects of drugs and network modifications

Patent trolls, litigation and the market for innovation

We examine the role of non-practicing entities (NPEs), often called patent trolls, in patent litigation. We present a theoretical model that predicts that cases with NPE patentees resolve faster. We test this prediction using a hand-collected data set of US patent litigation cases. We find that NPEs challenge larger and more technology intensive firms, and use more valuable patents from technology areas that have a less fragmented ownership base compared to the control group. Controlling for these factors, we find that NPE cases are indeed resolved faster. NPEs help to increase the speed of diffusion of technology into the economy; therefore, increasing the effectiveness of the market for innovation. Keywords: litigation, patents, patent trolls, technology diffusion

Perspective Hypergraphs and Cellular Networks

The understanding of biological networks is a fundamental issue in computational biology. When analyzing topological properties of networks, one often tends to substitute the term ‘‘network’ ’ for ‘‘graph’’, or uses both terms interchangeably. From a mathematical perspective, this is often not fully correct, because many functional relationships in biological networks are more complicated than what can be represented in graphs. In general, graphs are combinatorial models for representing relationships (edges) between certain objects (nodes). In biology, the nodes typically describe proteins

Nutzung eines Fahrermodells und regelungstechnischer Methoden zur Gestaltung einer Mensch-Maschine Schnittstelle für zukünftige Rollführungsprozesse

Um künftigen Kapazitätsengpässen im Luftverkehr entgegenzuwirken ist in den nächsten Jahren weltweit eine radikale Umstellung der boden- und luftseitigen Prozesse notwendig. Dieser Paradigmenwechsel ist unabdingbar mit der Einführung einer vierdimensionalen Steuerung aller Flugzeuge verbunden. Die verwendeten raum- und zeitfesten 4D-Trajektorien müssen von der Cockpitbesatzung umgesetzt werden um den optimalen Verkehrsfluss zu erreichen. Während eine Erweiterung des Autopiloten und des Flight Management Systems um die vierte zeitliche Dimension für die En Route Phase vorgesehen ist, ist eine Beibehaltung des Piloten als Agent im Rollprozess vorzuziehen. Eine Möglichkeit dazu stellt die Verwendung einer automatischen Befeuerung auf dem Rollfeld dar. Der Pilot folgt hierbei einer dem Flugzeug vorauslaufenden grünen Linie, gebildet aus Befeuerungselementen am Boden. In dieser Arbeit wird ein Ansatz dargestellt um die optimale Position der letzten befeuerten Lampe mit Hilfe der Methoden der Regelungstechnik zu berechnen. Hierzu wurde anhand eines verfügbaren Fahrermodells zur Verfolgung eines vorausfahrenden Fahrzeugs ein Regler ausgelegt. Pilotenverhalten und Flugzeugdynamik bilden in diesem Ansatz die Regelstrecke. Der Eingang der Regelstrecke ist der Abstand der letzten befeuerten Lampe zum Flugzeug, der Ausgang ist die Flugzeugposition. Der Regler berechnet aus der Differenz zwischen vorgegebener 4D-Trajektorie und aktueller Flugzeugposition eine optimierte Befeuerung des Rollfeldes. Ein Vergleich mit einer reinen Steuerung der Befeuerung zeigt die Vorteile der vorgestellten Methode. Insbesondere bei gegebener Varianz der Verhaltensmuster der Piloten zeigt die Regelung deutliche Vorteile gegenüber einer Steuerung