Radiogenomic modeling predicts survival-associated prognostic groups in glioblastoma is a research paper published in Neuro-Oncology Advances (2021). On theSindex it has a DataRank of 0. It has been cited 6 times.
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National Science Foundation
Grant: DGE-1762114]
National Institutes of Health
Grant: K08 CA245037]
NCI NIH HHS
Grant: K08 CA245037
National Institutes of Health
Grant: 5K08CA245037-02
CHARACTERIZING AGGRESSIVE GLIOMA COPY NUMBER SUBTYPES
National Science Foundation
Grant: 1762114
Graduate Research Fellowship Program (GRFP)
FWCI
0.70
Citation Percentile
0.7%
Citation Trend
Fields of Study
Keywords
Sustainable Development Goals
Additional file 2 of Machine learning modeling of genome-wide copy number alteration signatures reliably predicts IDH mutational status in adult diffuse glioma
Additional file 2 of Machine learning modeling of genome-wide copy number alteration signatures reliably predicts IDH mutational status in adult diffuse glioma
The Cancer Genome Atlas Glioblastoma Multiforme Collection (TCGA-GBM)