Abstract
The last two decades have witnessed impressive developments in the technology of genotyping and sequencing. Thousands of human DNA samples have been genotyped at increasing densities or sequenced in full using next generation DNA sequencing technology. The challenge is now to equip computational scientists with the right tools to go beyond mining genetic data to discover small gold nuggets and build models that can decipher the mechanism linking genotypes to phenotypes and can be used to identify subjects at risk for disease. We will discuss different approaches to model genetic data, and emphasize the need of blending a deep understanding of study design, with statistical modeling techniques and intelligent data approaches to make analysis feasible and results interpretable and useful.
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Sebastiani, P. (2012). Intelligent Data Analysis of Human Genetic Data. In: Hollmén, J., Klawonn, F., Tucker, A. (eds) Advances in Intelligent Data Analysis XI. IDA 2012. Lecture Notes in Computer Science, vol 7619. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34156-4_2
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DOI: https://doi.org/10.1007/978-3-642-34156-4_2
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