UNLABELLED: Gemma is a database, analysis software system and web site for genomics data re-use and meta-analysis. Currently, Gemma contains analyzed data from over 3300 expression profiling studies, yielding hundreds of millions of differential expression results and coexpression patterns (correlated expression) for retrieval and visualization. With optional registration users can save their own data and securely share it with other users. Web services and integration with third-party resources further increase the scope of the tools, which include a Cytoscape plugin. AVAILABILITY: http://chibi.ubc.ca/Gemma, Apache 2.0 license.

caBIGtrade (the cancer Biomedical Informatics Gridtrade) is an open-source, open-access information network enabling cancer researchers to share tools, data, applications, and technologies. caGrid is the underlying service-based grid software infrastructure for caBIG, integrating distributed data and analytic resources into a virtual collaborative platform for cancer research. Within caGrid, many cancer-related data analysis and aggregation tasks can make use of "canned" sets of service invocations, or workflows. As a result, there is a need to orchestrate the invocation of caGrid services through the use of both a workflow language and tooling. In this paper, we first explain why we select Taverna as a candidate for workflow authoring and invocation. We then review the development of Taverna plug-ins in general, and describe how we extend Taverna to use caGrid services. We then detail a real-world example and the lessons learned from our research. Finally we conclude with a summary and a description of potential next steps.

BACKGROUND: It is common for the results of a microarray study to be analyzed in the context of biologically-motivated groups of genes such as pathways or Gene Ontology categories. The most common method for such analysis uses the hypergeometric distribution (or a related technique) to look for "over-representation" of groups among genes selected as being differentially expressed or otherwise of interest based on a gene-by-gene analysis. However, this method suffers from some limitations, and biologist-friendly tools that implement alternatives have not been reported. RESULTS: We introduce ErmineJ, a multiplatform user-friendly stand-alone software tool for the analysis of functionally-relevant sets of genes in the context of microarray gene expression data. ErmineJ implements multiple algorithms for gene set analysis, including over-representation and resampling-based methods that focus on gene scores or correlation of gene expression profiles. In addition to a graphical user interface, ErmineJ has a command line interface and an application programming interface that can be used to automate analyses. The graphical user interface includes tools for creating and modifying gene sets, visualizing the Gene Ontology as a table or tree, and visualizing gene expression data. ErmineJ comes with a complete user manual, and is open-source software licensed under the Gnu Public License. CONCLUSION: The availability of multiple analysis algorithms, together with a rich feature set and simple graphical interface, should make ErmineJ a useful addition to the biologist's informatics toolbox. ErmineJ is available from http://microarray.cu.genome.org.