GRENAD, a Modular and Generic Smart-Grid Framework

ISSN 2300-5963International audienceWe present in this paper GRENAD, a Multi-Agent System based framework for the simulation and piloting of power-grids and particularly smart-grids. Exploiting a component-based approach, it allows a flexible design of complex smart-grid applications by providing a generic canvas where extensible, modular and reusable components, defined on the basis of their functionalities, can be easily combined and connected. Thanks to Multi-Agent approach, a set of such components can naturally be integrated into a coherent economical agent. GRENAD makes no assumption on the energy definition and eases the development of MAS control algorithms for smart-grids. The level of details of the energy-related information is controllable and this information is computed either through internal physical models or by interfacing with external simulators. We present here our model, illustrate its features with a rich example which exhibits its genericity, and demonstrate how a coordination protocol can easily be integrated to it

PeakForest: a spectral database and its toolbox, dedicated to the Metabolomics’ community

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Workflow4Metabolomics: an international computing infrastructure for Metabolomics

Thursday 4th July - Talks I & TrainingsProteomics & Metabolomics. Moderator: P. JagtapThe Workflow4Metabolomics (W4M) project aims to develop full LC/MS, GC/MS, FIA/MS and NMR pipelines using Galaxy framework for dataanalysis including preprocessing, normalization, quality control, statistical analysis and annotation steps. Our current developments aim to provide a set of interactive visualization tools in order to make ease the results interpretations. The development of Shiny applications will allows interactions from graphical features and dataset filters with graphical outputs like chromatograms, RMN spectra, heatmaps or PCA. In parallel, one of the major issue of the metabolomic approach is the compounds identification. To facilitate this annotation step, tandem mass spectrometry (MS/MS) is able to provide informations about the compounds structure. For that reason, an MS/MS data processing workflow based on msPurity, and two identification tools, metFrag and Sirius-CSI: FingerID, will be available in W4M

Create, run, share, publish, and reference your LC-MS, FIA-MS, GC-MS, and NMR data analysis workflows with the Workflow4Metabolomics 3.0 Galaxy online infrastructure for metabolomics

International audienceMetabolomics is a key approach in modern functional genomics and systems biology. Due to the complexity of metabolomics data, the variety of experimental designs, and the variety of existing bioinformatics tools, providing experimenters with a simple and efficient resource to conduct comprehensive and rigorous analysis of their data is of utmost importance. In 2014, we launched the Workflow4Metabolomics (W4M; http://workflow4metabolomics.org) online infrastructure for metabolomics built on the Galaxy environment, which offers user-friendly features to build and run data analysis workflows including preprocessing, statistical analysis, and annotation steps. Here we present the new W4M 3.0 release, which contains twice as many tools as the first version, and provides two features which are, to our knowledge, unique among online resources. First, data from the four major metabolomics technologies (i.e., LC-MS, FIA-MS, GC-MS, and NMR) can be analyzed on a single platform. By using three studies in human physiology, alga evolution, and animal toxicology, we demonstrate how the 40 available tools can be easily combined to address biological issues. Second, the full analysis (including the workflow, the parameter values, the input data and output results) can be referenced with a permanent digital object identifier (DOI). Publication of data analyses is of major importance for robust and reproducible science. Furthermore, the publicly shared workflows are of high-value for e-learning and training. The Workflow4Metabolomics 3.0 e-infrastructure thus not only offers a unique online environment for analysis of data from the main metabolomics technologies, but it is also the first reference repository for metabolomics workflows