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Table 4 Bayesian Wnt pathway from [1]

From: A pedagogical walkthrough of computational modeling and simulation of Wnt signaling pathway using static causal models in MATLAB

Bayesian Wnt pathway. Three static models have been developed based on particular gene set measured for human colorectal cancer cases [2]. Available epigenetic data for individual gene is also recorded. For sake of simplicity, the models are connoted as \(\mathcal {M}_{\text {PBK+EI}}\) (model with prior biological knowledge (PBK) and epigenetic information (EI)), \(\mathcal {M}_{\text {PBK}}\) (model with PBK only), and \(\mathcal {M}_{\text {NB+MPBK}}\) (model with naive Bayes (NB) formulation and minimal PBK). All models are simple directed acyclic graphs (DAG) with nodes and edges. Figure 2 shows a detailed influence diagram of \(\mathcal {M}_{\text {PBK+EI}}\) between the nodes and the edges. The nodes specify status of gene expression (D K K1, D K K2, D K K3-1, D K K3-2, D K K4, D A C T1, D A C T2, D A C T3, S F R P1, S F R P2, S F R P3, S F R P4, S F R P5, W I F1, MYC, C D44, C C N D1, and L E F1), methylation (M e D A C T1, M e D A C T2, M e S F R P1, M e S F R P2, M e S F R P4, M e S F R P5, M e D K K1, M e D K K4, and M e W I F1), histone marks for DACT3 (H3K27m e3 and H3K4m e3), transcription complex TRCMPLX, samples Sample and factors involved in formation of TRCMPLX like β-catenin, T C F4, and L E F1. Note that there were two recordings of gene expression D K K3 and thus were distinguished by D K K3−1 and D K K3−2. Some causal relations are based on prior biological knowledge and others are based on assumptions, elucidation of which follows in the next section.