Meta-analysis of muscle transcriptome data using the MADMuscle database reveals biologically relevant gene patterns

<p>Abstract</p> <p>Background</p> <p>DNA microarray technology has had a great impact on muscle research and microarray gene expression data has been widely used to identify gene signatures characteristic of the studied conditions. With the rapid accumulation of muscle microarray data, it is of great interest to understand how to compare and combine data across multiple studies. Meta-analysis of transcriptome data is a valuable method to achieve it. It enables to highlight conserved gene signatures between multiple independent studies. However, using it is made difficult by the diversity of the available data: different microarray platforms, different gene nomenclature, different species studied, etc.</p> <p>Description</p> <p>We have developed a system tool dedicated to muscle transcriptome data. This system comprises a collection of microarray data as well as a query tool. This latter allows the user to extract similar clusters of co-expressed genes from the database, using an input gene list. Common and relevant gene signatures can thus be searched more easily. The dedicated database consists in a large compendium of public data (more than 500 data sets) related to muscle (skeletal and heart). These studies included seven different animal species from invertebrates (<it>Drosophila melanogaster, Caenorhabditis elegans</it>) and vertebrates (<it>Homo sapiens, Mus musculus, Rattus norvegicus, Canis familiaris, Gallus gallus</it>). After a renormalization step, clusters of co-expressed genes were identified in each dataset. The lists of co-expressed genes were annotated using a unified re-annotation procedure. These gene lists were compared to find significant overlaps between studies.</p> <p>Conclusions</p> <p>Applied to this large compendium of data sets, meta-analyses demonstrated that conserved patterns between species could be identified. Focusing on a specific pathology (Duchenne Muscular Dystrophy) we validated results across independent studies and revealed robust biomarkers and new pathways of interest. The meta-analyses performed with MADMuscle show the usefulness of this approach. Our method can be applied to all public transcriptome data.</p

Comparison of global analysis technique and direct evaluation of capsizing probability on French frigates

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Layer-by-layer assembly for biofunctionalization of cellulosic fibers with emergent antimicrobial agents

Series title: Advances in polymer science series, ISSN 0065-3195, vol. 271Coating with polyelectrolyte multilayers has become a generic way to functionalize a variety of materials. In particular, the layer-by-layer (LbL) technique allows the coating of solid surfaces to give them several functionalities, including controlled release of bioactive agents. At present there are a large number of applications of the LbL technique; however, it is still little explored in the area of textiles. In this review we present an overview of LbL for textile materials made from synthetic or natural fibers. More specifically, LbL is presented as a method for obtaining new bioactive cotton (as in cellulosic fibers) for potential application in the medical field. We also review recent progress in the embedding of active agents in adsorbed multilayers as a novel way to provide the system with a “reservoir” where bioactive agents can be loaded for subsequent release.The authors would like to thank Fundação para a Ciência e Tecnologia (FCT) for the funding granted for the project PTDC/EBB-BIO/113671/2009 (FCOMP-01-0124-FEDER- 014752) Skin2Tex. Also, we would like to thank Fundo Europeu de Desenvolvimento Regional (FEDER) through COMPETE – Programa Operacional Factores de Competitividade (POFC) for co-funding