Multi-Class Protein Fold Prediction Using Stochastic Logic Programs
نویسندگان
چکیده
This paper presents an application of stochastic logic programs (SLPs) to learning probabilistic logic rules in protein fold prediction. We apply SLP parameter estimation algorithm to a previous study in which rules have been learned by inductive logic programming (ILP). On the basis of experiments, we demonstrate that probabilistic ILP approaches (eg. SLPs) have advantages for solving multi-class protein fold prediction problems and SLPs have outperformed ILP plus majority class predictor in both predictive accuracy and result interpretability.
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