4,492 research outputs found

    Handling oversampling in dynamic networks using link prediction

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    Oversampling is a common characteristic of data representing dynamic networks. It introduces noise into representations of dynamic networks, but there has been little work so far to compensate for it. Oversampling can affect the quality of many important algorithmic problems on dynamic networks, including link prediction. Link prediction seeks to predict edges that will be added to the network given previous snapshots. We show that not only does oversampling affect the quality of link prediction, but that we can use link prediction to recover from the effects of oversampling. We also introduce a novel generative model of noise in dynamic networks that represents oversampling. We demonstrate the results of our approach on both synthetic and real-world data.Comment: ECML/PKDD 201

    Determining Principal Component Cardinality through the Principle of Minimum Description Length

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    PCA (Principal Component Analysis) and its variants areubiquitous techniques for matrix dimension reduction and reduced-dimensionlatent-factor extraction. One significant challenge in using PCA, is thechoice of the number of principal components. The information-theoreticMDL (Minimum Description Length) principle gives objective compression-based criteria for model selection, but it is difficult to analytically applyits modern definition - NML (Normalized Maximum Likelihood) - to theproblem of PCA. This work shows a general reduction of NML prob-lems to lower-dimension problems. Applying this reduction, it boundsthe NML of PCA, by terms of the NML of linear regression, which areknown.Comment: LOD 201

    Positive Semidefiniteness and Positive Definiteness of a Linear Parametric Interval Matrix

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    We consider a symmetric matrix, the entries of which depend linearly on some parameters. The domains of the parameters are compact real intervals. We investigate the problem of checking whether for each (or some) setting of the parameters, the matrix is positive definite (or positive semidefinite). We state a characterization in the form of equivalent conditions, and also propose some computationally cheap sufficient\,/\,necessary conditions. Our results extend the classical results on positive (semi-)definiteness of interval matrices. They may be useful for checking convexity or non-convexity in global optimization methods based on branch and bound framework and using interval techniques

    Brain immune cells undergo cGAS-STING-dependent apoptosis during herpes simplex virus type 1 infection

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    Protection of the brain from viral infections involves the type I interferon (IFN-I) system, defects in which renders humans susceptible to herpes simplex encephalitis (HSE). However, excessive cerebral IFN-I levels leads to pathologies, suggesting the need for tight regulation of responses. Based on data from mouse models, human HSE cases, and primary cell culture systems, we here show that microglia and other immune cells undergo apoptosis in the HSV-1-infected brain through a mechanism dependent on the cyclic GMP-AMP synthase (cGAS) - stimulator of interferon genes (STING) pathway, but independent of IFN-I. HSV-1 infection of microglia induced cGAS-dependent apoptosis at high viral doses, while lower viral doses led to IFN-I responses. Importantly, inhibition of caspase activity prevented microglial cell death and augmented IFN-I responses. Accordingly, HSV-1-infected organotypic brain slices, or mice treated with caspase inhibitor, exhibited lower viral load and improved outcome of infection. Collectively, we identify an activation-induced apoptosis program in brain immune cells which down-modulates local immune responses

    Structural insight into SUMO chain recognition and manipulation by the ubiquitin ligase RNF4

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    The small ubiquitin-like modifier (SUMO) can form polymeric chains that are important signals in cellular processes such as meiosis, genome maintenance and stress response. The SUMO-targeted ubiquitin ligase RNF4 engages with SUMO chains on linked substrates and catalyses their ubiquitination, which targets substrates for proteasomal degradation. Here we use a segmental labelling approach combined with solution nuclear magnetic resonance (NMR) spectroscopy and biochemical characterization to reveal how RNF4 manipulates the conformation of the SUMO chain, thereby facilitating optimal delivery of the distal SUMO domain for ubiquitin transfer
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