Figure 1.

Context-Mining process flow. The process to analyze heterogeneous biological data to learn context-specific gene regulations is illustrated in this figure. We first identify context-motifs using crosstalk, conditioning and statistical p-value computations. Since some genes can be a driver in a context motif, but a passenger in other context motifs, these context motifs can be chained together to build a interaction graph. In this graph, each edge represents an interaction specific to certain subset of samples (context motif). We now use this property along with graph clustering to identify potential cellular contexts where we should see a set of interactions sharing significant numbers of samples in common. Once cellular contexts are identified, we annotate each context (which includes a subset of samples and a subset of genes) using gene enrichment, subtype enrichment, or survival analysis methods as described in the paper.