BACKGROUND: High throughput techniques are becoming more and more important in many areas of basic and applied biomedical research. Microarray techniques using cDNAs or oligonucleotides are such high throughput approaches for large-scale gene expression analysis and enable the investigation of mechanisms of fundamental processes and the molecular basis of diseases on a genomic scale. Microarray experiments have been used to identify differentially expressed genes in a highly parallel manner. Beyond simple discrimination of differentially expressed genes, functional annotation of coexpressed genes (guilt-by-association), diagnostic classification, and investigation of regulatory mechanisms (coregulation from coexpression) require clustering of genes into sets with similar expression patterns. In collaboration with The Institute for Genomic Research (TIGR), Rockville, MD/USA, we have recently developed a versatile, comprehensive, portable and easy to use JAVA tool (Quackenbush J. Computational Analysis of Microarray Data. Nat. Genet. Rev., 2:418-427, 2001) for large-scale gene expression studies. The implemented clustering and classification procedures in combination with the appropriate filtering, normalization, and similarity distance measurement, enable researchers to analyse the data in a systematic and reproducible way for a given set of experiments. However, presently the software has to be installed on a high-end NT/UNIX platforms...(this text has been cut automatically)
|Tatsächlicher Beginn/ -es Ende||15/12/01 → 31/12/02|
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