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The development in measurement and data collection technologies have made it possible to gather and store large amount of information in many areas of science and industry. The ability to analyze these masses of raw data has increased at a much slower speed, however. The group develops data mining and computational statistics methods for various application tasks.
The work concentrates on algorithmic and foundational issues of data mining, e.g., on the analysis of large discrete data sets.
The Data Mining group in Otaniemi conducts research on finding local patterns and global models in discrete high-dimensional data.
The group develops computational methods for use in medical molecular genetics, including genetic association analysis, haplotype analysis and reconstruction, utilisation of haplotype blocks and SNPs. We do close collaboration with several research groups in medical genetics.
The work is focused on developing computational methods for analyzing gene expression data produced by microarrays and complemented by other sources of data, e.g. clinical patient data and chromosomal locations of genes. The group has active collaboration with biologists and medical reserachers.