Visualizing metabolic network dynamics through time-series metabolomic data

摘要

Over the last few decades, new technological developments have enabled the generation of vast amounts of “-omics” data [ ]. These various -omic data types have helped bring new insights to a vast array of biological questions [ – ]. As more and more data are generated, however, researchers are faced with the enormous challenge of integrating, interpreting, and visualizing these data. The community has recognized these needs, focusing efforts on data visualization as a way to maximize the utility of biological data [ ]. Data visualization is particularly crucial for a systems-level perspective of metabolic networks and pathways. Several excellent software tools were made available for drawing and exploring biological network graphs [ – ]. These tools provide impressive descriptions of the network and support for diverse analyses, including the mapping of omics data to networks. In this study, we present GEM-Vis as a new approach for the visualization of time-course metabolomic data in the context of large-scale metabolic network maps.