Profiling the Nanoparticles Associated Metabolic Pathways

To explore the nanoparticles-dependent signaling pathways is a rapidly growing research field. Here, we globally elucidate the regulation modules of cellular molecules by using graph-based representation of complex networks. We have packed some useful bioinformatics methods (Matlab Simbiology and Pathway Studio) into an integrated system for graphbased representation and complex networks modeling. Here, this system is applied to the public literature and microarray database of nanoparticles and try to find out nanoparticles related genetic regulatory pathways. By comparing to different model organism system (bacteria, mice, cell line), we will establish a multidimensional (protein cellular location, time course expression pattern and chemicals interacting profiles) secondary database. The value added database will uncover some new relationships between genes and nanoparticles and provide useful information for the modeling of nanoparticles cellular regulatory pathway in an interactive form. The new modeling approaches should serve as a research platform to find protein candidates for nanoparticles associated diseases and provides a possible cue to improve the bio-chemo-informatics analyses on gene expression and molecular pharmacology.