Software Development

We are activly developing and implementing statistical methods to analyze genomic data and are making these available in public domain software.

Software development is often done within the open Bioconductor platform for the statistical computing environment of R. Several R-Packages have been developed by the group: "arrayMagic" for standardized workflows in microarray analysis (Buness 2005); "MCRestimate" for the evaluation of classification methods (Ruschhaupt 2004); "sagenhaft" for the analysis of SAGE data (Beißbarth 2004); "Prada" for the analysis of cellular assays (Hahne 2006); "gosim" to compare functional annotations of genes (Fröhlich 2007); "Quantpro" for the analysis of protein array data (Korf 2008); "nem" to reconstruct biological pathways from data (Fröhlich 2008).

Further, several web interfaces were developed. The software GOstat makes it possible to detect significantly overrepresented GO-terms in gene lists (Beißbarth 2004). LifeDB has been developed for the analysis and dissemination of data from protein localization and cellular assays (Mehrle 2006).

Training and consultancy ensures the wide applicability of the developed software. We coordinated the highly successful training courses for Practical Microarray Analysis.

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