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The dataset contains features from 386 TCGA tumors for modeling ecDNA cargo gene prediction. It was converted from R data format with the following code. NOTE: columns 'sample' and 'gene_id' are not used for actual modeling but for identifying, and sampling purposes. library(data.table) data = readRDS("~/../Downloads/ecDNA_cargo_gene_modeling_data.rds") colnames(data)[3] = "total_cn" data.table::fwrite(data, file = "~/../Downloads/ecDNA_cargo_gene_modeling_data.csv.gz", sep = ",")
PCAWG, machine learning, TCGA, ecDNA
PCAWG, machine learning, TCGA, ecDNA
| 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). | 0 | |
| 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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| downloads | 6 |

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