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Predicting clinical outcomes in neuroblastoma with genomic data integration
2018
Biology Direct
Neuroblastoma is a heterogeneous disease with diverse clinical outcomes. Current risk group models require improvement as patients within the same risk group can still show variable prognosis. Recently collected genome-wide datasets provide opportunities to infer neuroblastoma subtypes in a more unified way. Within this context, data integration is critical as different molecular characteristics can contain complementary signals. To this end, we utilized the genomic datasets available for the
doi:10.1186/s13062-018-0223-8
pmid:30621745
pmcid:PMC6889397
fatcat:qavn3bpxzjdpld375zjtg3eczm