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Table 1 Performance comparison between the model with gene expression data alone and models identified using knowledge-based matrices

From: Knowledge-driven genomic interactions: an application in ovarian cancer

Data type

Balanced accuracy

AUC

Gene expression

0.6957

0.7103

Pathway

0.7451

0.7457

GO

0.6991

0.7275

Pfam

0.7046

0.7335

Integration

0.7882

0.8108

  1. We compare here our results of evaluating gene-expression data alone, KEGG, GO, Pfam, and integration modeling. The integration model was developed by combining variables from KEGG pathway-based matrix, GO-based matrix, and Pfam-based matrix. Performances were measured based on the balanced accuracy and area under the ROC curve (AUC).
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BioData Mining

ISSN: 1756-0381