234 research outputs found

    Flexible constrained sampling with guarantees for pattern mining

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    Pattern sampling has been proposed as a potential solution to the infamous pattern explosion. Instead of enumerating all patterns that satisfy the constraints, individual patterns are sampled proportional to a given quality measure. Several sampling algorithms have been proposed, but each of them has its limitations when it comes to 1) flexibility in terms of quality measures and constraints that can be used, and/or 2) guarantees with respect to sampling accuracy. We therefore present Flexics, the first flexible pattern sampler that supports a broad class of quality measures and constraints, while providing strong guarantees regarding sampling accuracy. To achieve this, we leverage the perspective on pattern mining as a constraint satisfaction problem and build upon the latest advances in sampling solutions in SAT as well as existing pattern mining algorithms. Furthermore, the proposed algorithm is applicable to a variety of pattern languages, which allows us to introduce and tackle the novel task of sampling sets of patterns. We introduce and empirically evaluate two variants of Flexics: 1) a generic variant that addresses the well-known itemset sampling task and the novel pattern set sampling task as well as a wide range of expressive constraints within these tasks, and 2) a specialized variant that exploits existing frequent itemset techniques to achieve substantial speed-ups. Experiments show that Flexics is both accurate and efficient, making it a useful tool for pattern-based data exploration.Comment: Accepted for publication in Data Mining & Knowledge Discovery journal (ECML/PKDD 2017 journal track

    Microbial carbon metabolism associated with electrogenic sulphur oxidation in coastal sediments

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    Recently, a novel electrogenic type of sulphur oxidation was documented in marine sediments, whereby filamentous cable bacteria (Desulfobulbaceae) are mediating electron transport over cm-scale distances. These cable bacteria are capable of developing an extensive network within days, implying a highly efficient carbon acquisition strategy. Presently, the carbon metabolism of cable bacteria is unknown, and hence we adopted a multidisciplinary approach to study the carbon substrate utilization of both cable bacteria and associated microbial community in sediment incubations. Fluorescence in situ hybridization showed rapid downward growth of cable bacteria, concomitant with high rates of electrogenic sulphur oxidation, as quantified by microelectrode profiling. We studied heterotrophy and autotrophy by following 13C-propionate and -bicarbonate incorporation into bacterial fatty acids. This biomarker analysis showed that propionate uptake was limited to fatty acid signatures typical for the genus Desulfobulbus. The nanoscale secondary ion mass spectrometry analysis confirmed heterotrophic rather than autotrophic growth of cable bacteria. Still, high bicarbonate uptake was observed in concert with the development of cable bacteria. Clone libraries of 16S complementary DNA showed numerous sequences associated to chemoautotrophic sulphur-oxidizing Epsilon- and Gammaproteobacteria, whereas 13C-bicarbonate biomarker labelling suggested that these sulphur-oxidizing bacteria were active far below the oxygen penetration. A targeted manipulation experiment demonstrated that chemoautotrophic carbon fixation was tightly linked to the heterotrophic activity of the cable bacteria down to cm depth. Overall, the results suggest that electrogenic sulphur oxidation is performed by a microbial consortium, consisting of chemoorganotrophic cable bacteria and chemolithoautotrophic Epsilon- and Gammaproteobacteria. The metabolic linkage between these two groups is presently unknown and needs further study

    An index to quantify an individual's scientific research output that takes into account the effect of multiple coauthorship

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    I propose the index ā„\hbar ("hbar"), defined as the number of papers of an individual that have citation count larger than or equal to the ā„\hbar of all coauthors of each paper, as a useful index to characterize the scientific output of a researcher that takes into account the effect of multiple coauthorship. The bar is higher for ā„\hbar.Comment: A few minor changes from v1. To be published in Scientometric

    Large oncosomes contain distinct protein cargo and represent a separate functional class of tumor-derived extracellular vesicles

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    Large oncosomes (LO) are atypically large (1-10 mu m diameter) cancer-derived extracellular vesicles (EVs), originating from the shedding of membrane blebs and associated with advanced disease. We report that 25% of the proteins, identified by a quantitative proteomics analysis, are differentially represented in large and nano-sized EVs from prostate cancer cells. Proteins enriched in large EVs included enzymes involved in glucose, glutamine and amino acid metabolism, all metabolic processes relevant to cancer. Glutamine metabolism was altered in cancer cells exposed to large EVs, an effect that was not observed upon treatment with exosomes. Large EVs exhibited discrete buoyant densities in iodixanol (OptiPrep (TM)) gradients. Fluorescent microscopy of large EVs revealed an appearance consistent with LO morphology, indicating that these structures can be categorized as LO. Among the proteins enriched in LO, cytokeratin 18 (CK18) was one of the most abundant (within the top 5th percentile) and was used to develop an assay to detect LO in the circulation and tissues of mice and patients with prostate cancer. These observations indicate that LO represent a discrete EV type that may play a distinct role in tumor progression and that may be a source of cancer-specific markers.1182Ysciescopu

    The hw-rank: an h-index variant for ranking web pages

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    We introduce a novel ranking of search results based on a variant of the h-index for directed information networks such as the Web. The h-index was originally introduced to measure an individual researcherā€™s scientific output and influence, but here a variant of it is applied to assess the ā€˜ā€˜importanceā€™ā€™ of web pages. Like PageRank, theā€˜ā€˜importanceā€™ā€™ of a page is defined by the ā€˜ā€˜importanceā€™ā€™ of the pages linking to it. However, unlike the computation of PageRank which involves the whole web graph, computing the h-index for web pages (the hw-rank) is based on a local computation and only the neighbors of the neighbors of the given node are considered. Preliminary results show a strong correlation between ranking with the hw-rank and PageRank, and moreover its computation is simpler and less complex than computation of the PageRank. Further, larger scale experiments are needed in order to assess the applicability of the method
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