Non Parametric Predictive Modeling of Large Scale Data

Student: Giri Chandadevi

Educational Programme: Big Data Systems (Master)

Year of Graduation: 2017

The goal of the present research is to check the hypothesis that DNA structures contribute to cancerogenesis. To find an answer to this fundamental question the following tasks were formulated: - perform genome-wide association analysis between a distribution of cancer mutations (point mutations and break points) and stem-loop structures - find patterns of high correlations - apply methods of unsupervised learning to find patterns of correlations - build a non-parametric model that will predict densities of DNA structures distributions based on cancer breakpoints

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