Figure 1.

Schematic chart for mining breast cancer genes. Four different types of data were used as input: PPI data, human gene expression data, known breast cancer genes and GO annotations. Gene expression data (GDSes) from the GEO database were clustered. Known breast cancer genes and their enriched GO annotations were used to rank genes in those clusters. From the PPI network, three network topological attributes were computed to rank genes in the network. Finally, all individual rankings were combined into a final rank, which represents a gene’s overall probability of being involved in breast cancer.