PheNetic : network-based interpretation of molecular profiling data

Molecular profiling experiments have become standard in current wet-lab practices. Classically, enrichment analysis has been used to identify biological functions related to these experimental results. Combining molecular profiling results with the wealth of currently available interactomics data, however, offers the opportunity to identify the molecular mechanism behind an observed molecular phenotype. In this paper, we therefore introduce 'PheNetic', a userfriendly web server for inferring a sub-network based on probabilistic logical querying. PheNetic extracts from an interactome, the sub-network that best explains genes prioritized through a molecular profiling experiment. Depending on its run mode, PheNetic searches either for a regulatorymechanism that gave explains to the observed molecular phenotype or for the pathways (in) activated in the molecular phenotype. The web server provides access to a large number of interactomes, making sub-network inference readily applicable to a wide variety of organisms. The inferred sub-networks can be interactively visualized in the browser. PheNetic's method and use are illustrated using an example analysis of differential expression results of ampicillin treated Escherichia coli cells. The PheNetic web service is available at http://bioinformatics.intec.ugent.be/phenetic/

TMEM106B is associated with frontotemporal lobar degeneration in a clinically diagnosed patient cohort

In a genome-wide association study of frontotemporal lobar degeneration with pathological inclusions of TAR DNA-binding protein, significant association was obtained with three single nucleotide polymorphisms at 7p21.3, in a region encompassing the gene TMEM106B. This study also suggested a potential modifying effect of TMEM106B on disease since the association was strongest in progranulin mutation carriers. Further, the risk effect seemed to correlate with increased TMEM106B expression in patients. In the present study, we sought to replicate these three findings using an independent Flanders–Belgian cohort of primarily clinically diagnosed patients with frontotemporal lobar degeneration (n = 288). We were able to confirm the association with TMEM106B with a P-value of 0.008 for rs1990622, the top marker from the genome-wide association study [odds ratio 0.75 (95% confidence interval 0.61–0.93)]. Further, high-density single nucleotide polymorphism mapping suggested that the association was solely driven by the gene TMEM106B. Homozygous carriers of the TMEM106B protective alleles had a 50% reduced risk of developing frontotemporal lobar degeneration. However, we were unable to detect a modifying effect of the TMEM106B single nucleotide polymorphisms on onset age in progranulin mutation carriers belonging to an extended, clinical and pathological well-documented founder family segregating a progranulin null mutation. Also, we could not observe significant differences in messenger RNA expression between patients and control individuals in lymphoblast cell lines and in brain frontal cortex. In conclusion, we replicated the genetic TMEM106B association in a primarily clinically diagnosed cohort of patients with frontotemporal lobar degeneration from Flanders–Belgium. Additional studies are needed to unravel the molecular role of TMEM106B in disease onset and pathogenesis

k-Optimal: A novel approximate inference algorithm for ProbLog

ProbLog is a probabilistic extension of Prolog. Given the complexity of exact inference under ProbLog’s semantics, in many applications approximate inference is necessary. Current approximate inference algorithms for ProbLog however require either dealing with large numbers of proofs or do not guarantee a low approximation error. In this paper we introduce a new approximate inference algorithm which addresses these shortcomings. Given a user-specified parameter k, this algorithm approximates the success probability of a query based on at most k proofs and ensures that the calculated probability p is (1 − 1/e)p* <= p <= p* , where p* is the highest probability that can be calculated based on any set of k proofs. Furthermore a useful feature of the set of calculated proofs is that it is diverse. We show that this type of inference is in particular useful in solving decision problems.status: publishe

k -Optimal: A novel approximate inference algorithm for ProbLog

status: publishe

k-optimal: A novel approximate inference algorithm for ProbLog

ProbLog is a probabilistic extension of Prolog. Given the complexity of exact inference under ProbLog’s semantics, in many applications in machine learning approximate inference is necessary. Current approximate inference algorithms for ProbLog however require either dealing with large numbers of proofs or do not guarantee a low approximation error. In this paper we introduce a new approximate inference algorithm which addresses these shortcomings. Given a user-specified parameter k, this algorithm approximates the success probability of a query based on at most k proofs and ensures that the calculated probability p is (1 − 1/e)p ∗ ≤ p ≤ p ∗ , where p ∗ is the highest probability that can be calculated based on any set of k proofs. Furthermore a useful feature of the set of calculated proofs is that it is diverse. Our experiments show the utility of the proposed algorithm.status: publishe

Het lokaal woonbeleid op (de) kaart! De praktijk van het lokaal woonbeleid beschreven, de subsidie voor intergemeentelijke samenwerking geëvalueerd,

Dit onderzoek schetst een gedetailleerd beeld van de praktijk van het lokale woonbeleid in Vlaanderen en de effecten van de subsidie voor intergemeentelijke samenwerking. Ten opzichte van 2006 is een sterk toegenomen dynamiek op vlak van lokaal woonbeleid zichtbaar. Een ander belangrijk verschil met de situatie in 2006 is dat toen grote verschillen bestonden tussen gemeenten naargelang de verstedelijkingsgraad, waarbij het vaak alleen de centrumsteden waren die bepaalde taken opnamen. In 2015 stellen we voor veel van de lokaal woonbeleidsdomeinen geen belangrijke verschillen meer vast tussen de typen van gebieden. De niet‐stedelijke gebieden, en in het bijzonder de gemeenten van het platteland, hebben daarmee een sterke inhaalbeweging uitgevoerd. Dit is vooral zichtbaar op vlak van het ontwikkelen van een beleidsvisie en de coördinerende rol van de gemeente. Hoewel er grote vooruitgang is geboekt, is wel nog progressie mogelijk. De subsidie lokaal woonbeleid lijkt hierbij te werken als een stimulerend instrumenten. De gunstige beoordeling van de effectiviteit van de subsidie lokaal woonbeleid biedt een argument om dit subsidie‐instrument ook in de toekomst verder te blijven inzetten.nrpages: 198status: publishe