Abstract
Today, nobody can contest that the amount and complexity of scientific data are increasing exponentially. In life sciences, the unique conjunction of complexity, size and importance of available data deserves special attention in both Web Information Systems (WIS) and data integration and mining areas. In the last few years, WIS have become the favourite mean for offering open access to biological data. Hundreds of data sources (databases with either user or program interface), numerous web sites and peer-reviewed literature are currently covering multiple facets of biology (genomic sequences, protein structures, pathways, transcriptomics data, etc.). However, the scientists have enormous difficulties in keeping up with this data deluge. The effective and efficient management and use of available data (including omics data), and in particular the transformation of these data into information and knowledge, is a key requirement for success in scientific discovery process. In fact, the bottlenecks for life sciences have shifted from data production to data access/integration, pre-processing, analysis/mining, and interpretation.
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