10 research outputs found

    High Performance Pre-Computing: Prototype Application to a Coastal Flooding Decision Tool

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    International audienceAfter defining the High Performance Pre- Computing --referred as HPPC-- concept, the aim of the present study is to develop a prototype whether to approve or not the benefits of this concept. Our application case tries to answer the geophysical issue of coastal flooding. This is an example of an alert system based on the HPPC architecture, thus on pre-computed scenarios. The prototype provides the scientists with an ergonomic and on-demand tool allowing the run of scenarios of any implemented numerical models. These runs are available through a web application which submits the corresponding jobs on the remote french public cluster of HPC@LR. In this study we simulate the waves propagation over a Mediterranean grid using the wave model WaveWatch III⃝R . A reference simulation using usual conditions is approximated using the k-NN algorithm over 12, 98 and then 980 pre-computed scenarios. This simple experiment demonstrates how useful the pre-computing of scenarios is for alert systems as far as enough and relevant scenarios are pre-computed. This is the reason why searches continue in each critical points of the HPPC architecture such as the design of experiment, the approximation of the results by meta-models and the research of the closest scenarios in this big data context

    The Translational Medicine Ontology and Knowledge Base: driving personalized medicine by bridging the gap between bench and bedside

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    Background: Translational medicine requires the integration of knowledge using heterogeneous data from health care to the life sciences. Here, we describe a collaborative effort to produce a prototype Translational Medicine Knowledge Base (TMKB) capable of answering questions relating to clinical practice and pharmaceutical drug discovery. Results: We developed the Translational Medicine Ontology (TMO) as a unifying ontology to integrate chemical, genomic and proteomic data with disease, treatment, and electronic health records. We demonstrate the use of Semantic Web technologies in the integration of patient and biomedical data, and reveal how such a knowledge base can aid physicians in providing tailored patient care and facilitate the recruitment of patients into active clinical trials. Thus, patients, physicians and researchers may explore the knowledge base to better understand therapeutic options, efficacy, and mechanisms of action. Conclusions: This work takes an important step in using Semantic Web technologies to facilitate integration of relevant, distributed, external sources and progress towards a computational platform to support personalized medicine. Availability: TMO can be downloaded from http://code.google.com/p/translationalmedicineontology and TMKB can be accessed at http://tm.semanticscience.org/sparql

    MOESM1 of PubChemRDF: towards the semantic annotation of PubChem compound and substance databases

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    Additional file 1. The supporting information for the paper entitled: PubChemRDF: towards the semantic annotation of PubChem compound and substance databases

    The RNA Ontology (RNAO): An Ontology for Integrating RNA Sequence and Structure Data

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    Biomedical Ontologies integrate diverse biomedical data and enable intelligent data-mining and help translate basic research into useful clinical knowledge. We present the RNA Ontology (RNAO), an ontology for integrating diverse RNA data, including RNA sequences and sequence alignments, three-dimensional structures, and biochemical and functional data. For example, individual atomic resolution RNA structures have broader significance as representatives of classes of homologous molecules, which can differ significantly in sequence while sharing core structural features and common roles or functions. Thus, structural data gain value by being linked to homologous sequences in genomic data and databases of sequence alignments. Likewise, the value of genomic data is enhanced by annotation of shared structural features, especially when these can be linked to specific functions. Moreover, the significance of biochemical, functional and mutational analyses of RNA molecules are most fully understood when linked to molecular structures and phylogenies. To achieve these goals, RNAO provides logically rigorous definitions of the components of RNA primary, secondary and tertiary structure and the relations between these entities. RNAO is being developed to comply with the developing standards of the Open Biomedical Ontologies (OBO) Consortium. The RNAO can be accessed at http://code.google.com/p/rnao/

    Eosinophils Reduce Chronic Inflammation in Adipose Tissue by Secreting Th2 Cytokines and Promoting M2 Macrophages Polarization

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    Obesity is now recognized as a low-grade, chronic inflammatory disease that is linked to a myriad of disorders including cardiovascular diseases, type 2 diabetes, and liver diseases. Recently it is found that eosinophils accelerate alternative activation macrophage (AAM) polarization by secreting Th2 type cytokines such as interleukin-4 and interleukin-13, thereby reducing metainflammation in adipose tissue. In this review, we focused on the role of eosinophils in regulating metabolic homeostasis and obesity
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