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It has become common ground to start a bioinformatics article by mentioning the flood of data overwhelming the research community. Indeed, the large amount of data has led to the insight that even the average wet lab needs several computers, e.g. to manage micro array results or to run BLAST searches via the internet.However, it is more than that: bioinformatics has matured to a research discipline in its own right. The main reason is that bioinformatics not only allows for the solving of problems that are tedious in a traditional approach (e.g. protein function can often be inferred from homologous proteins in other species), but contributes to a new way of looking at biological systems: from a reductionist approach, to a systemic view of biology (Noble 2002).With the large amounts of data on whole systems, the focus in biomedical research is increasing steadily: from a single protein to complexes, from an enzyme-catalyzed reaction to metabolic networks.Even virtual cells or tissues are no longer science fiction. Recently, the term bioinformatics has been used more and more to describe research related to databases (integration of resources, web access, etc.) and sequence analysis (homology searches,multiple sequence alignments, phylogenetic trees).Computational biology refers to the simulation of complex networks, e.g. metabolic or signalling pathways, cell and tissue simulations. In recent years, the field has seen an -omics explosion (e.g. genomics, proteomics, transcriptomics, metabolomics), five of which have created several research communities eager to integrate their data. [ABSTRACT FROM AUTHOR]

The assignment of nuclear Overhauser effect (NOE) resonances is the crucial step in determining the three-dimensional structure of biomolecules from nuclear magnetic resonance (NMR) data. Our program, Ambiguous Retraints for Iterative Assignment (ARIA), treats Noe assignment as an integral part of the structure determination process. This chapter briefly outlines the method and discusses how to carry out a complete structure determination project with the new version 2.0 of ARIA. Two new features greatly streamline the procedure: a new graphical user interface (GUI) and the incorporation of the data model of the Collaborative Computing Project for the NMR community (CCPN). The GUI supports the user in setting up and managing a project. The CCPN data model facilitates data exchange with a great variety of other programs. We give practical guidelines for how to use ARIA and how to analyze results. [ABSTRACT FROM AUTHOR]