Probabilistic Paths for Protein Complex Inference

摘要: Understanding how individual proteins are organized into complexes and pathways is a significant current challenge. We introduce new algorithms to infer protein by combining seed with confidence-weighted network. Two stochastic methods use averaging over probabilistic ensemble of networks, the deterministic method provides ranking prospective complex members. compare performance these three existing algorithms. test algorithm using weighted graphs: naive Bayes estimate probability direct stable protein-protein interaction; logistic regression or indirect decision tree whether two exist within common complex. The best-performing in trials methods. significantly faster, whereas less sensitive weighting scheme.