110 research outputs found

    Digital Repositories and the Semantic Web: Semantic Search and Navigation for DSpace

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    4th International Conference on Open RepositoriesThis presentation was part of the session : DSpace User Group PresentationsDate: 2009-05-21 08:30 AM – 10:00 AMIn many digital repository implementations, resources are often described against some flavor of metadata schema, popularly the Dublin Core Element Set (DCMES), as is the case with the DSpace system. However, such an approach cannot capture richer semantic relations that exist or may be implied, in the sense of a Semantic Web ontology. Therefore we first suggest a method in order to semantically intensify the underlying data model and develop an automatic translation of the flatly organized metadata information to this new ontology. Then we propose an implementation that provides for inference-based knowledge discovery, retrieval and navigation on top of digital repositories, based on this ontology. We apply this technique to real information stored in the University of Patras Institutional Repository that is based on DSpace, and confirm that more powerful, inference-based queries can indeed be performed

    Socratic dialogue as a teaching and research method for co-creativity?

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    We sketch a theory of creativity which centres on the framing of activity by repetitive thinking and action, and sees creativity as divergences from these routines which is thereby framed against them. Without a repetitive frame creativity is impossible. Mere repetition is not creative, even if new. Creativity disrupts a frame, purposefully. Socratic Dialogue is an ancient technique of engaging a student in a dialogue by asking non-leading questions, aimed at revealing to the student how much knowledge he or she already has on some topic: Socrates’ demonstration to the slave-boy (and the audience) that the boy already knows geometry (without any schooling) is the founding example. We aim to illustrate that internalising the Socratic kind of reflective self-questioning and co-questioning is intimately related to the view of creativity as the reframing of routine. Therefore, we have qualitatively analysed primary and secondary school pilots in Greece, Austria and the United Kingdom. The illustrations of facilitated Socratic Dialogues with children and young people have been derived from the analysis of 14 Socratic Dialogues involving a total number of 97 students. This paper outlines the Socratic Dialogue as a method of both researching and teaching creative thinking, and it reveals that the Socratic method dovetails with this conception of co-creativity. As a research method, Socratic Dialogue aims to elicit information concerning reasoning processes and shared experiences. As a teaching method, Socratic Dialogue aims to get students to internalise the public methodology of Socratic Dialogue, and to adopt it across the range of domains they meet. The students’ use of the internalised method towards enabling creative thinking is illustrated by the experiences of the teaching intervention teams in the C2Learn project, using games to provide occasions for co-creativity

    On the Limitations of Manipulation Checks: An Obstacle Toward Cumulative Science

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    Manipulation checks do not allow ruling out or accepting alternative explanations of causal effects (Sigall & Mills, 1998). In order to gauge the influence of this argument on current research practices, we surveyed the views of researchers on manipulation checks. Results confirmed that a manipulation check still stands as a totem of experimental rigor. Except in rare circumstances, such as when pilot testing, manipulation checks do not provide information relevant to construct validity. While it seems cost free to include seemingly informative manipulation checks, we claim it is actually costly because it wrongly enhances subjective confidence in the validity of research findings. We conclude that manipulation checks may hinder efforts to adopt a cumulative culture and practice of hypothesis testing

    Identification of drug-specific pathways based on gene expression data: application to drug induced lung injury

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    Identification of signaling pathways that are functional in a specific biological context is a major challenge in systems biology, and could be instrumental to the study of complex diseases and various aspects of drug discovery. Recent approaches have attempted to combine gene expression data with prior knowledge of protein connectivity in the form of a PPI network, and employ computational methods to identify subsets of the protein–protein-interaction (PPI) network that are functional, based on the data at hand. However, the use of undirected networks limits the mechanistic insight that can be drawn, since it does not allow for following mechanistically signal transduction from one node to the next. To address this important issue, we used a directed, signaling network as a scaffold to represent protein connectivity, and implemented an Integer Linear Programming (ILP) formulation to model the rules of signal transduction from one node to the next in the network. We then optimized the structure of the network to best fit the gene expression data at hand. We illustrated the utility of ILP modeling with a case study of drug induced lung injury. We identified the modes of action of 200 lung toxic drugs based on their gene expression profiles and, subsequently, merged the drug specific pathways to construct a signaling network that captured the mechanisms underlying Drug Induced Lung Disease (DILD). We further demonstrated the predictive power and biological relevance of the DILD network by applying it to identify drugs with relevant pharmacological mechanisms for treating lung injury.Institute for Collaborative Biotechnologies (Grant W911NF-09-0001

    A crowd-sourcing approach for the construction of species-specific cell signaling networks

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    Motivation: Animal models are important tools in drug discovery and for understanding human biology in general. However, many drugs that initially show promising results in rodents fail in later stages of clinical trials. Understanding the commonalities and differences between human and rat cell signaling networks can lead to better experimental designs, improved allocation of resources and ultimately better drugs. Results: The sbv IMPROVER Species-Specific Network Inference challenge was designed to use the power of the crowds to build two species-specific cell signaling networks given phosphoproteomics, transcriptomics and cytokine data generated from NHBE and NRBE cells exposed to various stimuli. A common literature-inspired reference network with 220 nodes and 501 edges was also provided as prior knowledge from which challenge participants could add or remove edges but not nodes. Such a large network inference challenge not based on synthetic simulations but on real data presented unique difficulties in scoring and interpreting the results. Because any prior knowledge about the networks was already provided to the participants for reference, novel ways for scoring and aggregating the results were developed. Two human and rat consensus networks were obtained by combining all the inferred networks. Further analysis showed that major signaling pathways were conserved between the two species with only isolated components diverging, as in the case of ribosomal S6 kinase RPS6KA1. Overall, the consensus between inferred edges was relatively high with the exception of the downstream targets of transcription factors, which seemed more difficult to predict. Contact: [email protected] or [email protected]. Supplementary information: Supplementary data are available at Bioinformatics onlin

    A crowd-sourcing approach for the construction of species-specific cell signaling networks

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    Motivation: Animal models are important tools in drug discovery and for understanding human biology in general. However, many drugs that initially show promising results in rodents fail in later stages of clinical trials. Understanding the commonalities and differences between human and rat cell signaling networks can lead to better experimental designs, improved allocation of resources and ultimately better drugs. Results: The sbv IMPROVER Species-Specific Network Inference challenge was designed to use the power of the crowds to build two species-specific cell signaling networks given phosphoproteomics, transcriptomics and cytokine data generated from NHBE and NRBE cells exposed to various stimuli. A common literature-inspired reference network with 220 nodes and 501 edges was also provided as prior knowledge from which challenge participants could add or remove edges but not nodes. Such a large network inference challenge not based on synthetic simulations but on real data presented unique difficulties in scoring and interpreting the results. Because any prior knowledge about the networks was already provided to the participants for reference, novel ways for scoring and aggregating the results were developed. Two human and rat consensus networks were obtained by combining all the inferred networks. Further analysis showed that major signaling pathways were conserved between the two species with only isolated components diverging, as in the case of ribosomal S6 kinase RPS6KA1. Overall, the consensus between inferred edges was relatively high with the exception of the downstream targets of transcription factors, which seemed more difficult to predict. Contact: [email protected] or [email protected]. Supplementary information: Supplementary data are available at Bioinformatics online

    MAPK pathway and B cells overactivation in multiple sclerosis revealed by phosphoproteomics and genomic analysis

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    Dysregulation of signaling pathways in multiple sclerosis (MS) can be analyzed by phosphoproteomics in peripheral blood mononuclear cells (PBMCs). We performed in vitro kinetic assays on PBMCs in 195 MS patients and 60 matched controls and quantified the phosphorylation of 17 kinases using xMAP assays. Phosphoprotein levels were tested for association with genetic susceptibility by typing 112 single-nucleotide polymorphisms (SNPs) associated with MS susceptibility. We found increased phosphorylation of MP2K1 in MS patients relative to the controls. Moreover, we identified one SNP located in the PHDGH gene and another on IRF8 gene that were associated with MP2K1 phosphorylation levels, providing a first clue on how this MS risk gene may act. The analyses in patients treated with disease-modifying drugs identified the phosphorylation of each receptor’s downstream kinases. Finally, using flow cytometry, we detected in MS patients increased STAT1, STAT3, TF65, and HSPB1 phosphorylation in CD19+ cells. These findings indicate the activation of cell survival and proliferation (MAPK), and proinflammatory (STAT) pathways in the immune cells of MS patients, primarily in B cells. The changes in the activation of these kinases suggest that these pathways may represent therapeutic targets for modulation by kinase inhibitors

    Machine learning and data mining frameworks for predicting drug response in cancer:An overview and a novel <i>in silico</i> screening process based on association rule mining

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