BACKGROUND: Bioinformatics is confronted with a new data explosion due to the availability of high throughput DNA sequencers. Data storage and analysis becomes a problem on local servers, and therefore it is needed to switch to other IT infrastructures. Grid and workflow technology can help to handle the data more efficiently, as well as facilitate collaborations. However, interfaces to grids are often unfriendly to novice users. RESULTS: In this study we reused a platform that was developed in the VL-e project for the analysis of medical images. Data transfer, workflow execution and job monitoring are operated from one graphical interface. We developed workflows for two sequence alignment tools (BLAST and BLAT) as a proof of concept. The analysis time was significantly reduced. All workflows and executables are available for the members of the Dutch Life Science Grid and the VL-e Medical virtual organizations All components are open source and can be transported to other grid infrastructures. CONCLUSIONS: The availability of in-house expertise and tools facilitates the usage of grid resources by new users. Our first results indicate that this is a practical, powerful and scalable solution to address the capacity and collaboration issues raised by the deployment of next generation sequencers. We currently adopt this methodology on a daily basis for DNA sequencing and other applications. More information and source code is available via http://www.bioinformaticslaboratory.nl/

Summary: Although whole-genome sequences have been analysed for the presence of anomalous DNA, no dedicated application is currently available to analyse the composition of individual sequence entries, for instance those derived by experimental techniques, such as subtractive hybridization. Since genomic dinucleotide frequency values are conserved between related species, a representative genome sequence can often be found to score for anomalous sequence composition for many of these putative horizontally transferred sequences. We developed the application δρ-web, which enables the determination of the differences between the dinucleotide composition of an input sequence and that of a selected genome in a size-dependent manner. A feature allowing batch comparisons is included as well. In addition, δρ-web allows the analysis of the dinucleotide composition of complete genomes. This provides complementary information for the identification of large anomalous gene clusters. Availability: The application is available through http://deltarho.amc.uva.nl and the software is available from the authors. Contact: [email protected] Supplementary information An online help file with more extensive user guidelines is supplied at http://deltarho.amc.uva.nl

Abstract Motivation: To enhance the exploration of gene expression data in a metabolic context, one requires an application that allows the integration of this data and which represents this data in a (genome-wide) metabolic map. The layout of this metabolic map must be highly flexible to enable discoveries of biological phenomena. Moreover, it must allow the simultaneous representation of additional information about genes and enzymes. Since the layout and properties of existing maps did not fulfill our requirements, we developed a new way of representing gene expression data in metabolic charts. Results: ViMAc generates user-specified (genome-wide) metabolic maps to explore gene expression data. To enhance the interpretation of these maps information such as sub-cellular localization is included. ViMAc can be used to analyse human or yeast expression data obtained with DNA microarrays or SAGE. We introduce our metabolic map method and demonstrate how it can be applied to explore DNA microarray data for yeast. Availability: ViMAc is freely available for academic institutions on request from the authors. Contact: [email protected] * To whom correspondence should be addressed.