Article ID Journal Published Year Pages File Type
10225729 Big Data Research 2018 10 Pages PDF
Abstract
We run experiments on DNA methylation datasets extracted from The Cancer Genome Atlas, focusing on three tumor types: breast, kidney, and thyroid carcinomas. We perform classifications extracting several methylated sites and their associated genes with accurate performance (accuracy >97%). Results suggest that BIGBIOCL can perform hundreds of classification iterations on hundreds of thousands of features in few hours. Moreover, we compare the performance of our method with other state-of-the-art classifiers and with a wide-spread DNA methylation analysis method based on network analysis. Finally, we are able to efficiently compute multiple alternative classification models and extract - from DNA-methylation large datasets - a set of candidate genes to be further investigated to determine their active role in cancer. BIGBIOCL, results of experiments, and a guide to carry on new experiments are freely available on GitHub at https://github.com/fcproj/BIGBIOCL.
Related Topics
Physical Sciences and Engineering Computer Science Computational Theory and Mathematics
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