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berTool, GenomeHistory, GeneDirector, DCGrid 5.0, Avaki 2.5, CAGED


Cologne-based startup Science Factory has made a release candidate of its ÜberTool enterprise bioinformatics software available to interested users. ÜberTool uses a biological object model to integrate public and proprietary data sources, analytical applications, and visualization tools.


GenomeHistory, a software tool that locates duplicate genes, is available from the University of New Mexico department of biology at: /soft ware/ GenomeHistory. According to its developers, the software identifies all pairs of duplicate genes in a genome and then determines the degree of synonymous and non-synonymous divergence between each duplicate pair. GenomeHistory is released under the Gnu GPL. WU-Blast and ClustalW are required packages.


BioDiscovery of Marina Del Ray, Calif., has released version 2.0 of GeneDirector, a data analysis and LIMS system for microarray research. GeneDirector offers sample and array tracking, project management, and Oracle database-enabled versions of the company’s CloneTracker array layout software, ImaGene image analysis software, and GeneSight statistical data analysis and visualization software. GeneDirector supports microarray data from spotted array technologies, Affymetrix GeneChip data, and data from the Agilent 2100 Bioanalyzer product line.


Entropia of San Diego has released DCGrid 5.0, the latest version of its PC grid computing platform. Features include an open platform; binary-level integration for native 32-bit Windows applications; a patent-pending protection technology; and a Web-based job workflow management interface. Meanwhile, Avaki of Cambridge, Mass., released Avaki 2.5, the new version of its commercial grid software. The update includes enhanced caching mechanisms that increase data grid performance, the company said.


The Harvard Medical School informatics program at Children’s Hospital in Boston has introduced CAGED (Cluster Analysis of Gene Expression Dynamics), a new program for temporal analysis of gene expression data. The program uses Bayesian clustering by dynamics, a method that identifies the most probable set of clusters for a given time series. For more information, go to http://geno

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