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Bioinformatics tools for the systems biology of dysferlin deficiency

Abstract : The aim of this project was to build and apply tools for the analysis of muscle omics data, with a focus on Dysferlin deficiency. This protein is expressed mainly in skeletal and cardiac muscles, and its loss due to mutation (autosomal-recessive) of the DYSF gene, results in a progressive muscular dystrophy (Limb Girdle Muscular Dystrophy type 2B (LGMD2B), Miyoshi myopathy and distal myopathy with tibialis anterior onset (DMAT)). We have developed various tools and pipelines that can be applied towards a bioinformatics functional analysis of omics data in muscular dystrophies and neuromuscular disorders. These include: tests for enrichment of gene sets derived from previously published muscle microarray data and networking analysis of functional associations between altered transcripts/proteins. To accomplish this, we analyzed hundreds of published omics data from public repositories. The tools we developed are called CellWhere and MyoMiner. CellWhere is a user-friendly tool that combines protein-protein interactions and protein subcellular localizations on an interactive graphical display (https://cellwhere-myo.rhcloud.com). MyoMiner is a muscle cell- and tissue-specific database that provides co-expression analyses in both normal and pathological tissues. Many gene co-expression databases already exist and are used broadly by researchers, but MyoMiner is the first muscle-specific tool of its kind (https://myominer-myo.rhcloud.com). These tools will be used in the analysis and interpretation of transcriptomics data from dysferlinopathic muscle and other neuromuscular conditions and will be important to understand the molecular mechanisms underlying these pathologies.
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Apostolos Malatras. Bioinformatics tools for the systems biology of dysferlin deficiency. Quantitative Methods [q-bio.QM]. Université Pierre et Marie Curie - Paris VI, 2017. English. ⟨NNT : 2017PA066627⟩. ⟨tel-01996499⟩

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