Overview page is Under Development as of April 18, 2013

Proposed Initiative

This project aims to develop software that researchers can use to create interactive dynamic representations of cell signaling pathways that contain accurate structural details for improved communication and hypothesis generation. The software will function in a variety of popular interfaces, including web browsers, to enable researchers from any background to easily access and use the tools with no special training. Megan Riel-Mehan (graduating from Kevan Shokat’s lab in QB3) will pare down, clean up, merge and build upon generalized tools currently developed at QB3 to create an intuitive cell signaling visualization and modeling app we call sigViz.


Cells respond to their environment by integrating external signals into a directed response, such as whether or not to grow, move, differentiate, or attack a neighboring cell. Cells accomplish this through a tightly regulated and complex system of signaling molecules. As researchers rapidly identify more interactions, our knowledge of signaling pathways greatly extends, however, the data becomes more convoluted and more difficult to study or convey. Although programs exist that can store vast amounts of data and graph the interactions in networks, these programs generally produce visualizations that non-specialists find difficult to interpret (see fig 1A). New insights often occur when a scientist has an intuitive grasp of a system, and because visualization tools facilitate intuition, programs like Chimera and Cytoscape have become invaluable to structural and systems biologists respectively. This project aims to merge the core capabilities of a molecular viewer and a bioinformatics visualization platform–currently developed independently at QB3–together with a graphic user interface designed for quantitative biologists and outputs that target diverse audiences and purposes (journals, slides, websites, thought/virtual experiment tools).