Knowledge-guided fuzzy logic modeling to infer cellular signaling networks from proteomic data

About Knowledge-guided fuzzy logic network model Knowledge-guided fuzzy logic network model is a new hybrid method to integrate the prior knowledge and data-driven learning for signaling pathway inference. It is applied to infer signaling pathways by exploiting both prior knowledge and time-series data. In particular, the dynamic time warping algorithm is employed to measure the goodness of fit between experimental and predicted data, so that the method can model temporally-ordered experimental observations. Download Three datasets (Synthetic dataset, DREAM4 dataset and Cell fate prediction dataset) that are used to evaluate the model are available for downloading in this dataset record. The datasets can also be downloaded at: Github. Supplementary material: "Supplementary File: Knowledge-guided fuzzy logic modeling to infer cellular signaling networks from proteomic data".