1,521 research outputs found

    Gene-network inference by message passing

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    The inference of gene-regulatory processes from gene-expression data belongs to the major challenges of computational systems biology. Here we address the problem from a statistical-physics perspective and develop a message-passing algorithm which is able to infer sparse, directed and combinatorial regulatory mechanisms. Using the replica technique, the algorithmic performance can be characterized analytically for artificially generated data. The algorithm is applied to genome-wide expression data of baker's yeast under various environmental conditions. We find clear cases of combinatorial control, and enrichment in common functional annotations of regulated genes and their regulators.Comment: Proc. of International Workshop on Statistical-Mechanical Informatics 2007, Kyot

    Gene-network inference by message passing

    Full text link
    The inference of gene-regulatory processes from gene-expression data belongs to the major challenges of computational systems biology. Here we address the problem from a statistical-physics perspective and develop a message-passing algorithm which is able to infer sparse, directed and combinatorial regulatory mechanisms. Using the replica technique, the algorithmic performance can be characterized analytically for artificially generated data. The algorithm is applied to genome-wide expression data of baker's yeast under various environmental conditions. We find clear cases of combinatorial control, and enrichment in common functional annotations of regulated genes and their regulators.Comment: Proc. of International Workshop on Statistical-Mechanical Informatics 2007, Kyot

    Gene-network inference by message passing

    Full text link
    The inference of gene-regulatory processes from gene-expression data belongs to the major challenges of computational systems biology. Here we address the problem from a statistical-physics perspective and develop a message-passing algorithm which is able to infer sparse, directed and combinatorial regulatory mechanisms. Using the replica technique, the algorithmic performance can be characterized analytically for artificially generated data. The algorithm is applied to genome-wide expression data of baker's yeast under various environmental conditions. We find clear cases of combinatorial control, and enrichment in common functional annotations of regulated genes and their regulators.Comment: Proc. of International Workshop on Statistical-Mechanical Informatics 2007, Kyot

    Universal cloning of continuous quantum variables

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    The cloning of quantum variables with continuous spectra is analyzed. A universal - or Gaussian - quantum cloning machine is exhibited that copies equally well the states of two conjugate variables such as position and momentum. It also duplicates all coherent states with a fidelity of 2/3. More generally, the copies are shown to obey a no-cloning Heisenberg-like uncertainty relation.Comment: 4 pages, RevTex. Minor revisions, added explicit cloning transformation, added reference

    Jamming in complex networks with degree correlation

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    We study the effects of the degree-degree correlations on the pressure congestion J when we apply a dynamical process on scale free complex networks using the gradient network approach. We find that the pressure congestion for disassortative (assortative) networks is lower (bigger) than the one for uncorrelated networks which allow us to affirm that disassortative networks enhance transport through them. This result agree with the fact that many real world transportation networks naturally evolve to this kind of correlation. We explain our results showing that for the disassortative case the clusters in the gradient network turn out to be as much elongated as possible, reducing the pressure congestion J and observing the opposite behavior for the assortative case. Finally we apply our model to real world networks, and the results agree with our theoretical model

    Multipartite entanglement for continuous variables: A quantum teleportation network

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    We show that {\it one} single-mode squeezed state distributed among NN parties using linear optics suffices to produce a truly NN-partite entangled state for any nonzero squeezing and arbitrarily many parties. From this NN-partite entangled state, via quadrature measurements of N−2N-2 modes, bipartite entanglement between any two of the NN parties can be `distilled', which enables quantum teleportation with an experimentally determinable fidelity better than could be achieved in any classical scheme.Comment: 4 pages, 2 figures, published version, paper shorter, title longe

    Quantum Dense Coding Exploiting Bright EPR Beam

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    Highly efficient quantum dense coding for continuous variables has been experimentally accomplished by means of exploiting bright EPR beam with anticorrelation of amplitude quadratures and correlation of phase quadratures, which is generated from a nondegenerate optical parametric amplifier operating in the state of deamplification. Two bits of classical information are encoded on two quadratures of a half of bright EPR beam at the sender Alice and transmitted to the receiver Bob via one qubit of the shared quantum state after encoding. The amplitude and phase signals are simultaneously decoded with the other half of EPR beam by the direct measurement of the Bell-state at Bob. The signal to noise ratios of the simultaneously measured amplitude and phase signals are improved 5.4dB and 4.8dB with respect to that of the shot noise limit respectively. A high degree of immunity to unauthorized eavesdropping of the presented quantum communication scheme is experimentally demonstrated.Comment: 11 pages, 5 figure
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