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EMMA 2 – A MAGE-compliant system for the collaborative analysis and integration of microarray data

Michael Dondrup, Stefan P Albaum, Thasso Griebel, Kolja Henckel, Sebastian Jünemann, Tim Kahlke, Christiane K Kleindt, Helge Küster, Burkhard Linke, Dominik Mertens, Virginie Mittard-Runte, Heiko Neuweger (+5 others)
2009 BMC Bioinformatics  
Understanding transcriptional regulation by genome-wide microarray studies can contribute to unravel complex relationships between genes. Attempts to standardize the annotation of microarray data include the Minimum Information About a Microarray Experiment (MIAME) recommendations, the MAGE-ML format for data interchange, and the use of controlled vocabularies or ontologies. The existing software systems for microarray data analysis implement the mentioned standards only partially and are often
more » ... hard to use and extend. Integration of genomic annotation data and other sources of external knowledge using open standards is therefore a key requirement for future integrated analysis systems. Results: The EMMA 2 software has been designed to resolve shortcomings with respect to full MAGE-ML and ontology support and makes use of modern data integration techniques. We present a software system that features comprehensive data analysis functions for spotted arrays, and for the most common synthesized oligo arrays such as Agilent, Affymetrix and NimbleGen. The system is based on the full MAGE object model. Analysis functionality is based on R and Bioconductor packages and can make use of a compute cluster for distributed services.
doi:10.1186/1471-2105-10-50 pmid:19200358 pmcid:PMC2645365 fatcat:vmficlw2vnfuvggnegr4zvyp5q

Plastid genomes of two brown algae, Ectocarpus siliculosus and Fucus vesiculosus: further insights on the evolution of red-algal derived plastids

Gildas Le Corguillé, Gareth Pearson, Marta Valente, Carla Viegas, Bernhard Gschloessl, Erwan Corre, Xavier Bailly, Akira F Peters, Claire Jubin, Benoit Vacherie, J Mark Cock, Catherine Leblanc
2009 BMC Evolutionary Biology  
Acknowledgements We are grateful to Alexander Goesmann and Virginie Mittard-Runte for providing access to the GenDB platform and to Hameed Khan and John M.  ... 
doi:10.1186/1471-2148-9-253 pmid:19835607 pmcid:PMC2765969 fatcat:fvopwmbsgrcvnlbs2vct4kw5ti