The primary remit of SMP-Bioinformatics is to facilitate the maximized utilisation and 'metamorphosis' of data from the NGFN2 initiative into expressions of biomedical knowledge. By providing the infrastructure and know-how necessary for this 'data to knowledge' transfer, we will play a key role in ensuring the success of NGFN2 as a whole. Our approach follows a concept of both centralized and decentralized data organization, manage­ment, analysis, interpretation and training. In so doing, we not only provide local support for the administration and analysis of experimental data, but also provide a comple­mentary systematic platform with centralized knowledge, tools and resources. In terms of generic organization, SMP Bioinformatics is founded on three distinct, albeit interdependent components. Together, these elements allow a so-called '3i-approach' to the data to knowledge transformation within the NGFN2 project =>1) Integrate, 2) Interpret and 3) Inform.

1. Integrate:

The first component, 'Data management', is responsible for the design, development, and provision of databases and standards for diverse data types. One of the primary remits is to accelerate the research pipeline of KGs by providing an appropriate database infrastructure and data integration tools, to facilitate the efficient and integrated management of multi-center research networks.

2. Interpret:

The second component, 'Data analysis', seeks to expand the focus beyond methods development for microarray analyses, to a more robust and comprehensive 'omic'-analysis suite. Important here will be the ability to meaningfully interpret data collected for the same clinical phenomenon on disparate technology platforms. With a network of information about the relationships between genes/proteins rapidly emerging, the analysis of functional data will therefore be facilitated within a functional context. This will include methods for vertical analyses across different genomic information levels and methods based on secondary network information. Further attention will be paid to the annotation and interpretation of results obtained by these methods, with the goal of producing high-quality primary annota­tions. To this end, data must be projected on functional modules, such as protein complexes, co-regulated genes, functional units such as mitochondria or ribosomes, metabolic and regulatory path­ways. While this concept has been successfully applied to model organisms such as yeast, the compre­hensive data resource to allow for the computational projection and interpretation of experimental data has yet to be developed. This will be achieved in our SMP by using homology-based methods for gene function annotation combined with advanced protein interaction prediction methods as well as bench­marked information transfer protocols.

3. Inform:

The third and final component, 'Consulting and Services', is responsible for the dissemination of methods, systems and know-how from the SMP Bioinformatics to other SMPs and KGs. Methods developed within the SMP Bioinformatics will be either distributed through the open-source toolbox system 'Bioconductor' or in ready-designed application specific workflows, through our proprietary process oriented data-mining platform MINE-IT. Existing know-how on study design, data analysis and data management will be disseminated through regular training courses, an extension of the very successful courses offered in NGFN1. Guidance to SMPs and KGs to achieve high quality in all aspects of an experiment will be provided, focusing on methodological quality and consulting. This subproject will be responsible for the definition, communication and application of methodological guidelines. Finally, comprehensive bioinformatics services on methods and tech­nologies represented within the present consortium will be provided by our consortium.

The subprojects and their interactions are presented in figure 1. For further details please visit the pages of the respective groups.

Figure 1: Image map of the correlation between the diverse subprojects of the SMP Bioinformatics