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This data set contains the clinical and genomics data for 1,420 subjects analyzed in the paper: Wong KY, Fan C, Tanioka M, Parker JS, Nobel AB, Zeng D, Lin DY, Perou CM. I-Boost: an integrative boosting approach for predicting survival time with multiple genomics platforms. Genome Biology. 2019. It contains data on time to death, cancer type, 4 clinical variables, expression of 12,434 genes, somatic mutation of 130 genes, expression of 305 miRNA, expression of 136 proteins or phospho-proteins, copy number of 216 DNA segments, and 497 gene expression modules. Data on time to death, clinical variables, somatic mutation, copy number variation, mRNA expression, and miRNA expression were derived from the pan-cancer data set at Synapse (syn2468297 at https://www.synapse.org/#!Synapse:syn2468297). The protein expression data were obtained from Broad GDAC Firehose (https://gdac.broadinstitute.org/runs/stddata__2016_01_28/).
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 1 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
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