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Relational Network for Knowledge Discovery through Heterogeneous Biomedical and Clinical Features
2016
Scientific Reports
Biomedical big data, as a whole, covers numerous features, while each dataset specifically delineates part of them. "Full feature spectrum" knowledge discovery across heterogeneous data sources remains a major challenge. We developed a method called bootstrapping for unified feature association measurement (BUFAM) for pairwise association analysis, and relational dependency network (RDN) modeling for global module detection on features across breast cancer cohorts. Discovered knowledge was
doi:10.1038/srep29915
pmid:27427091
pmcid:PMC4947904
fatcat:ngnr2gftwbgsvjh3delq3tkopi