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Fat&MuscleDB: A database to understand tissue growth processes contributing to body or muscle composition

Abstract : To minimise unnecessary redundancy in research efforts by a better use of available data, we present a web-based database and data-mining platform named Fat&MuscleDB. Genomics on muscle and adipose tissue growth has generated huge amount of data which are available in journals and in databases. Unfortunately these data are scattered on the Internet in a heterogeneous format. Thus, it is difficult to exploit them efficiently. We hypothesise that these data can allow identifying genes or proteins involved in adipose and muscle tissues development contributing to body or muscle composition, two key criteria of carcass and meat quality. Currently, Fat&MuscleDB contains genomic expression data and differential abundance data from about 100 publications and 75 GEO datasets. These data can be queried, visualised, and downloaded in different ways: the data visualisation of each reference, the search of transcripts or proteins in references, and the data aggregation based on criteria of adipose and muscle growth. The aggregation function of Fat&MuscleDB is illustrated through two questions: ''What are the proteins secreted by muscles?" and ''What are the transcripts and proteins involved in the growth of muscle tissue from genetic origins of bovine?''.
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https://hal.inrae.fr/hal-02739407
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Submitted on : Tuesday, June 2, 2020 - 9:54:59 PM
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  • HAL Id : hal-02739407, version 1
  • PRODINRA : 355189

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Jérémy Tournayre, Isabelle Cassar-Malek, Matthieu Reichstadt, Brigitte Picard, Nicolas Kaspric, et al.. Fat&MuscleDB: A database to understand tissue growth processes contributing to body or muscle composition. JOBIM 2015 - Journées Ouvertes Biologie Informatique Mathématiques, Jul 2015, Clermont-Ferrand, France. ⟨hal-02739407⟩

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