Numerous genomic annotations are currently stored in different Web-accessible databanks that scientists need to mine with user-defined queries and in a batch mode to orderly integrate the diverse extracted data in suitable user-customizable working environments. Unfortunately, to date, most accessible databanks can be interrogated only for a single gene or protein at a time and generally the data retrieved are available in HTML page format only. We developed GeneWebEx to effectively mine data of interest in different HTML pages of Web-interfaced databanks, and organize extracted data for further analyses. GeneWebEx utilizes user-defined templates to identify data to extract, and aggregates and structures them in a database designed to allocate the various extractions from distinct biomolecular databanks. Moreover, a template-based module enables automatic updating of extracted data. Validations performed on GeneWebEx allowed us to efficiently gather relevant annotations from various sources, and comprehensively query them to highlight significant biological characteristics.

Numerous genomic annotations are currently stored in different Web-accessible databanks that scientists need to mine with user-defined queries and in a batch mode to orderly integrate the diverse mined data in suitable user-customizable working environments. Unfortunately, to date, most accessible databanks can be interrogated only for a single gene or protein at a time and generally the data retrieved are available in HTML page format only. We developed GeneWebEx to effectively mine data of interest in different HTML pages of Web-based databanks, and organize extracted data for further analyses. Gene WebEx utilizes user-defined templates to identify data to extract, and aggregates and structures them in a database designed to allocate the various extractions from distinct biomolecular databanks. Moreover, a template-based module enables automatic updating of extracted data. Validations performed on GeneWebEx allowed us to efficiently gather relevant annotations from various sources, and comprehensively query them to highlight significant biological characteristics.

UNLABELLED: GenePicker allows efficient analysis of Affymetrix gene expression data performed in replicate, through definition of analysis schemes, data normalization, t-test/ANOVA, Change-Fold Change-analysis and yields lists of differentially expressed genes with high confidence. Comparison of noise and signal analysis schemes allows determining a signal-to-noise ratio in a given experiment. Change Call, Fold Change and Signal mean ratios are used in the analysis. While each parameter alone yields gene lists that contain up to 30% false positives, the combination of these parameters nearly eliminates the false positives as verified by northern blotting, quantitative PCR in numerous independent experiments as well as by the analysis of spike-in data. AVAILABILITY: http://www.ifom-firc.it/RESEARCH/Appl_Bioinfo/tools.html. SUPPLEMENTARY INFORMATION: http://www.ifom-firc.it/RESEARCH/Appl_Bioinfo/tools.html.

MOTIVATION: High-throughput technologies create the necessity to mine large amounts of gene annotations from diverse databanks, and to integrate the resulting data. Most databanks can be interrogated only via Web, for a single gene at a time, and query results are generally available only in the HTML format. Although some databanks provide batch retrieval of data via FTP, this requires expertise and resources for locally reimplementing the databank. RESULTS: We developed MyWEST, a tool aimed at researchers without extensive informatics skills or resources, which exploits user-defined templates to easily mine selected annotations from different Web-interfaced databanks, and aggregates and structures results in an automatically updated database. Using microarray results from a model system of retinoic acid-induced differentiation, MyWEST effectively gathered relevant annotations from various biomolecular databanks, highlighted significant biological characteristics and supported a global approach to the understanding of complex cellular mechanisms. AVAILABILITY: MyWEST is freely available for non-profit use at http://www.medinfopoli.polimi.it/MyWEST/

Abstract Summary: GAAS, Gene Array Analyzer Software supports multi-user efficient management and suitable analyses of large amounts of gene expression data across replicated experiments. Its management framework handles input data generated by different technologies. A multi-user environment allows each user to store his/her own data visualization scheme, analysis parameters used, values and formats of the output data. The analysis engine performs: background and spot quality evaluation, data normalization, differential gene expression analyses in single and multiple replica experiments. Results of expression profiles can be interactively navigated through graphical interfaces and stored into output databases. Availability: http://www.medinfopoli.polimi.it/GAAS/ Contact: [email protected] Supplementary information: http://www.medinfopoli.polimi.it/GAAS/ * To whom correspondence should be addressed.