SequencesViewer : comment rendre accessible des motifs séquentiels de gènes trop nombreux ?

National audienceLes techniques d'extraction de connaissances ppliquées aux gros volumes de données, issus de l'analyse de puces ADN, permettent de découvrir des connaissances jusqu'alors inconnues. Or, ces techniques produisent de très nombreux résultats, difficilement exploitables par les experts. Nous proposons un outil dédié à l'accompagnement de ces experts dans l'appropriation et l'exploitation de ces résultats. Cet outil est basé sur trois techniques de visualisation (nuages, systèmes solaire et treemap) qui permettent aux biologistes d'appréhender de grandes quantités de motifs séquentiels (séquences ordonnées de gènes)

Discovering Novelty in Gene Data : From Sequential Patterns to Visualization

International audienceData mining techniques allow users to discover novelty in huge amounts of data. Frequent pattern methods have proved to be efficient, but the extracted patterns are often too numerous and thus difficult to analyse by end-users. In this paper, we focus on sequential pattern mining and propose a new visualization system, which aims at helping end-users to analyse extracted nowledge and to highlight the novelty according to referenced biological document databases. Our system is based on two visualization techniques: Clouds and solar systems. We show that these techniques are very helpful for identifying associations and hierarchical relationships between patterns among related documents. Sequential patterns extracted from gene data using our system were successfully evaluated by two biology laboratories working on Alzheimers disease and cancer

SequenceViewer: Visualization of Genes Sequences

International audienceTechniques for extracting knowledge from huge volumes of biological data, obtained from DNA microarrays analysis, allow the discovery of previously unknown knowledge. How-ever, these techniques generally produce many results not easily actionable by the experts. We propose a tool dedicated to the support of these experts in the process of appropriation and exploitation of the knowledge obtained after the extrac-tion process. This tool is based on 3 visualization techniques (clouds, solar systems and treemap) that allow biologists to capture large amounts of patterns (ordered sequences of genes). These 3 visualizations are used to identify associations between group of patterns, the hierarchical relationships be-tween these patterns and the association of the sequences with the literature documents in order to ease the access to the publications, which deals about the genes of the patterns

Sequential patterns mining and gene sequence visualization to discover novelty from microarray data

International audienceData mining allow users to discover novelty in huge amounts of data. Frequent pattern methods have proved to be efficient, but the extracted patterns are often too numerous and thus difficult to analyze by end users. In this paper, we focus on sequential pattern mining and propose a new visualization system to help end users analyze the extracted knowledge and to highlight novelty according to databases of referenced biological documents. Our system is based on three visualization techniques: clouds, solar systems, and treemaps. We show that these techniques are very helpful for identifying associations and hierarchical relationships between patterns among related documents. Sequential patterns extracted from gene data using our system were successfully evaluated by two biology laboratories working on Alzheimer's disease and cancer

DBFrequentQueries: Extraction de requêtes fréquentes

National audienc

Primed antigen-specific CD4+ T cells are required for NK cell activation in vivo upon Leishmania major infection.

International audienceThe ability of NK cells to rapidly produce IFN-gamma is an important innate mechanism of resistance to many pathogens including Leishmania major. Molecular and cellular components involved in NK cell activation in vivo are still poorly defined, although a central role for dendritic cells has been described. In this study, we demonstrate that Ag-specific CD4(+) T cells are required to initiate NK cell activation early on in draining lymph nodes of L. major-infected mice. We show that early IFN-gamma secretion by NK cells is controlled by IL-2 and IL-12 and is dependent on CD40/CD40L interaction. These findings suggest that newly primed Ag-specific CD4(+) T cells could directly activate NK cells through the secretion of IL-2 but also indirectly through the regulation of IL-12 secretion by dendritic cells. Our results reveal an unappreciated role for Ag-specific CD4(+) T cells in the initiation of NK cell activation in vivo upon L. major infection and demonstrate bidirectional regulations between innate and adaptive immunity