the shuffle index and evaluation of models of signal transduction pathways
The development of algorithms that conjecture proteomic networks from sparse time series laboratory data is an open problem with much current interest. The development of indices that measure how well the conjectured proteomic network matches a literature model is also an open problem. In this paper, we apply a computational algebra algorithm ([1, 2, 3]) to chondrocyte signaling data ([14]). In order to compare our model to the literature, we combine data from protein isoforms or from proteins that have been phosphorylated at different sites by summing the associated data measurements. The algorithm produces an ordered list of network edges. The resulting cotemporal model is compared to a composite next-state model derived from Signal Transduction Knowledge Environment (STKE) sources. A shuffle index is used to determine how these results from the computational algorithm compare to the composite network.
shuffle index computational algebra game theory computational biology biological network modeling