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Biomarker discovery via dependency analysis of multi-view functional genomics data AbstractCancers are complex diseases, characterized by genomic changes at multiple levels of regulation. We present an integrative genome-wide approach that captures shared patterns from several data sources and extracts chromosomal regions predictive of patient survival in glioblastoma multiforme (GBM) progression and drug resistance. Our results identify known and novel genomic regions that may contribute to GBM progression and drug resistance.
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