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Addressing the Problems with Life-Science Databases For PERSPECTIVES 58. Lim, L. P. et al. Microarray analysis shows that 64. Dominski, Z. & Marzluff, W. F. Formation of the 3′ end Acknowledgements some microRNAs downregulate large numbers of histone mRNA. Gene 239, 1–14 (1999). We would like to thank S. Eddy for helpful comments and of target mRNAs. Nature 433, 769–773 65. Marzluff, W. F. Metazoan replication-dependent suggestions and D. Bartel, V. Ambros, R. Bock, M. Terns, (2005). histone mRNAs: a distinct set of RNA polymerase II L.A. Huber, P. Loidl, N. Polacek and laboratory members 59. Chan, S. W. et al. RNA silencing genes control de novo transcripts. Curr. Opin. Cell Biol. 17, 274–280 (2005). from the Division of Genomics and RNomics for critical read- DNA methylation. Science 303, 1336 (2004). 66. Nusinow, D. A. & Panning, B. Recognition and ing of the manuscript. The work discussed here was sup- 60. Aravin, A. A. et al. The small RNA profile during modification of sex chromosomes. Curr. Opin. Genet. ported by an Austrian FWF (Fonds zur Förderung der Drosophila melanogaster development. Dev. Cell 5, Dev. 15, 206–213 (2005). wissenschaftlichen Forschung) and a German DFG (Deutsche 337–350 (2003). 67. Chow, J. C., Yen, Z., Ziesche, S. M. & Brown, C. J. Forschungsgemeinschaft) grant to A.H. 61. Reinhart, B. J. & Bartel, D. P. Small RNAs correspond Silencing of the mammalian X chromosome. Annu. to centromere heterochromatic repeats. Science 297, Rev. Genomics Hum. Genet. 6, 69–92 (2005). Competing interests statement 1831 (2002). 68. Guthrie, C. & Patterson, B. Spliceosomal snRNAs. The authors declare no competing financial interests. 62. Cam, H. P. et al. Comprehensive analysis of Annu. Rev. Genet. 22, 387–419 (1998). heterochromatin- and RNAi-mediated epigenetic 69. Sharp, P. A. The discovery of split genes and RNA control of the fission yeast genome. Nature Genet. 37, splicing. Trends Biochem. Sci. 30, 279–281 (2005). FURTHER INFORMATION 809–819 (2005). 70. Ofengand, J. & Fournier, M. J. in Modification and Division of Genomics and RNomics, Innsbruck Biocenter: 63. Decatur, W. A. & Fournier, M. J. RNA-guided Editing of RNA (eds Grosjean, H. & Benne, R.) http://genomics.i-med.ac.at nucleotide modification of ribosomal and other RNAs. Ch. 12 (American Society for Microbiology Press, Access to this links box is available online. J. Biol. Chem. 278, 695–698 (2003). Washington DC, 1998). A common misconception is that the main OPINION problems of database integration are related to the technology that is used for these pur- Addressing the problems with poses. Here we argue that although the mas- tering of such technology can be challenging, the main problems are actually related to the life-science databases for traditional databases themselves. There are many issues with life-science databases that prevent the uses and systems biology effective use of integration technology. These problems not only have adverse effects on Stephan Philippi and Jacob Köhler the quintessential task of ensuring data avail- ability to the general research community, but Abstract | A prerequisite to systems biology is the integration of heterogeneous present an even greater obstacle to systems experimental data, which are stored in numerous life-science databases. However, biology. Here we provide a systematic analysis a wide range of obstacles that relate to access, handling and integration impede of the common problems that relate to life- the efficient use of the contents of these databases. Addressing these issues will science databases — which are technical, social and political — and suggest solutions not only be essential for progress in systems biology, it will also be crucial for for how they could be overcome. sustaining the more traditional uses of life-science databases. Technical problems Several decades ago, scientists started to respect to data accessibility. Furthermore, As a prerequisite for the discussion of tech- set up biological data collections for the the relatively new field of systems biology nical problems with life-science databases centralized management of and easy access has further increased the requirements that it is important to understand the general to experimental results, and to ensure long- are demanded of life-science databases. principles of database integration. Life- term data availability (FIG. 1a). Many early The general vision of systems biology is to science databases have experienced an expo- data collections were initially administered move out of the era of reductionist studies nential growth in numbers in recent years using word processing or spreadsheet of isolated parts of interest — for example, and contain information of many types7. To applications. Owing to the limited amount individual proteins and genes — and to bridge the gap between these often uncon- of data that could be stored in this way, and develop a molecular understanding of more nected islands of biological knowledge, and the reductionist viewpoint that character- complex structures and their dynamics, such between the different types of experimental ized most biological research at that time, as regulatory networks, cells, organs and, data that they contain, various approaches this approach to data collection seemed ultimately, whole organisms1. to data integration have been pursued reasonable, and was sufficient for occasional The most important tool for reaching over the past decade. These range from exchanges with colleagues. an understanding of biology at the level of basic hypertext linking to more advanced However, with the exponential growth systems is the analysis of biological models approaches that involve the use of federated of experimental data that is taking place (FIG. 1b). The basic building blocks for these databases and data warehouses (BOX 1). It is owing to rapid biotechnological advances models are existing experimental data, which on the advanced approaches that we focus and high-throughput technologies, as well are stored in literally thousands of data- here, as they provide the best illustration of as the advent of the World Wide Web as a bases2–4. As a result, database integration is a the diverse problems with life-science data- new means for data exchange, the world fundamental prerequisite for any study in sys- bases that affect data integration, particularly dramatically changed. The huge amounts of tems biology 5,6. Because database integration with respect to the goals of systems biology. data that are now produced on a daily basis has long been recognized as a key technology Although there are many variants of the require more sophisticated management in the life sciences, research in this area also more advanced applications, the problems solutions, and the availability of the internet has a long tradition. However, although many with life-science databases that affect inte- as a modern infrastructure for scientific approaches exist, database integration in the gration using federated database technology exchange has created new demands with life sciences is still far from being trivial. or data warehouses are almost identical. 482 | JUNE 2006 | VOLUME 7 www.nature.com/reviews/genetics © 2006 Nature Publishing Group PERSPECTIVES Here we use the popular data warehouse a Classical role of databases b New role of databases approach as an example. The typical steps in database integration that are followed in this Applications Applications approach are illustrated in FIG. 2. First, the databases to be integrated must be identified, and data must be extracted from the identi- Discovery Discovery fied sources. The extracted data are usually then preprocessed; for example, this can involve the conversion of data sources into more accessible formats such as XML. Source database structures are then mapped to a Hypotheses Experiments so-called integrated schema, which defines an integrated structure over all the data Biological models sources to be integrated (BOX 1). Finally, the Experiments data are imported into the data warehouse, where integrated access is made possible, Database Scientific for example, through a ‘browsable’ search integration databases interface. Scientific databases Here we provide a detailed discussion of the problems with life-science databases that Figure 1 | Classical and systems biology roles of life-science databases. The classical role of can occur at each stage of the data-integration life-science databases is to provide easy access to and long-term storage of experimental results, with process outlined above. centralized data management. By contrast, more recent systems biological approaches exploit the information in databases to generate hypotheses for in silico discovery, which, after experimental Web access problems. The first step in verification, can be used to populate other databases. building models for systems biology is the identification of suitable data sources. Therefore, a description of at least the In systems biology, the examination of concerns to political issues, as discussed database contents and the way in which isolated data entries usually provides little below. There are, however, a few databases the data are produced and/or derived insight, as it is the identification and discovery that allow access to life-science data with from other data sources is mandatory. of relationships between entries that is most ‘canned queries’ through the use of web Unfortunately, not every life-science data- important. Web-based browsing interfaces services8 as a more recent technical standard. base provides such
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