System-Level Modeling of Endothelial Permeability Pathway and High-throughput Data Analysis for Disease Biomarker Selection

Abstract

In my thesis, we developed an integrated model of thrombin-, histamine-, and VEGF-mediated MLC activation pathways. Detailed molecular interactions are specific and ordinary differential equations (ODEs) were used in our model to capture the time-dependent dynamic behavior of the concentration of proteins. The model was validated against a number of experimental findings. Also, it can be used to predict the effects of altered pathway components, collective actions of multiple mediators and the potential impact to various diseases.

Another perspective for deciphering the mechanism of endothelial permeability and related disease is identifying the gene markers responsible for disease initiation. To solve the problem of unstable biomarkers, we developed a novel gene selection method based on Support Vector Machines, recursive feature elimination, multiple random sampling strategies and multi-step evaluation of gene-ranking consistency.