| Title: | HISP: a hybrid intelligent approach for identifying directed signaling pathways |
| Address: | "Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai 200433, China. Department of Mathematics, Shanghai University, Shanghai 200444, China" |
| ISSN/ISBN: | 1759-4685 (Electronic) 1759-4685 (Linking) |
| Abstract: | "Signal transduction plays important roles in biological systems. Unfortunately, our knowledge about signaling pathways is far from complete. Specifically, the direction of signaling flows is less known even though the signaling molecules of some signaling pathways have been determined. In this paper, we propose a novel hybrid intelligent method, namely HISP (Hybrid Intelligent approach for identifying directed Signaling Pathways), to determine both the topologies of signaling pathways and the direction of signaling flows within a pathway based on integer linear programming and genetic algorithm. By integrating the protein-protein interaction, gene expression, and gene knockout data, our HISP approach is able to determine the optimal topologies of signaling pathways in an accurate way. Benchmark results on yeast MAPK signaling pathways demonstrate the efficiency of our proposed approach. When applied to the EGFR/ErbB signaling pathway in human hepatocytes, HISP unveils a high-resolution signaling pathway, where many signaling interactions were missing by existing computational approaches" |
| Keywords: | *Algorithms Cell Wall/metabolism Hepatocytes/metabolism Humans MAP Kinase Signaling System Pheromones/metabolism Protein Interaction Maps Saccharomyces cerevisiae/enzymology *Signal Transduction; |
| Notes: | "MedlineZhao, Xing-Ming Li, Shan eng Research Support, Non-U.S. Gov't 2017/12/28 J Mol Cell Biol. 2017 Dec 1; 9(6):453-462. doi: 10.1093/jmcb/mjx054" |
