Data Mining in the Life Sciences | Machine Learning for Personalized Medicine

Lecture by Karsten Borgwardt: Data Mining in the Life Sciences

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In this course, we will describe common data mining problems in the life sciences and state-of-the-art approaches for solving them. These problems include questions that arise traditionally in bioinformatics, such as sequence analysis and structural comparisons, and those which have been studied more recently, the inter-individual variation on the genetic and transcriptomic level and its link to phenotypic variation. We will describe how the combination of these two different branches of bioinformatics, molecule- and individual-centered bioinformatics, may pave the way to personalized medicine and which data mining problems have to be overcome along this way.