PROJECT TITLE :

P-Finder: Reconstruction of Signaling Networks from Protein-Protein Interactions and GO Annotations

ABSTRACT:

As a result of most advanced genetic diseases are caused by defects of cell signaling, illuminating a signaling cascade is essential for understanding their mechanisms. We have a tendency to gift three novel computational algorithms to reconstruct signaling networks between a starting protein and an ending protein using genome-wide protein-protein interaction (PPI) networks and gene ontology (GO) annotation information. A signaling network is represented as a directed acyclic graph during a merged kind of multiple linear pathways. An advanced semantic similarity metric is applied for weighting PPIs because the preprocessing of all three methods. The first algorithm repeatedly extends the list of nodes based mostly on path frequency towards an ending protein. The second algorithm repeatedly appends edges based mostly on the prevalence of network motifs that indicate the link patterns additional frequently appearing during a PPI network than in a very random graph. The last algorithm uses the knowledge propagation technique that iteratively updates edge orientations based mostly on the path strength and merges the chosen directed edges. Our experimental results demonstrate that the proposed algorithms achieve higher accuracy than previous strategies when they are tested on well-studied pathways of S. cerevisiae. Furthermore, we introduce an interactive internet application tool, called P-Finder, to visualize reconstructed signaling networks.