Abstract
We present a computational tool DSGRN for exploring network dynamics across the global parameter space for switching model representations of regulatory networks. This tool provides a finite partition of parameter space such that for each region in this partition a global description of the dynamical behavior of a network is given via a directed acyclic graph called a Morse graph. Using this method, parameter regimes or entire networks may be rejected as viable models for representing the underlying regulatory mechanisms.
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Acknowledgment
The work of T. G. was partially supported by NSF grants DMS-1226213 DMS-1361240 and DARPA D12AP200025. B. C. was supported by DARPA D12AP200025. The work of S. H. and K. M. was partially supported by grants NSF-DMS-1125174, 1248071, 1521771 and a DARPA contract HR0011-16-2-0033.
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Cummins, B., Gedeon, T., Harker, S., Mischaikow, K. (2017). Database of Dynamic Signatures Generated by Regulatory Networks (DSGRN). In: Feret, J., Koeppl, H. (eds) Computational Methods in Systems Biology. CMSB 2017. Lecture Notes in Computer Science(), vol 10545. Springer, Cham. https://doi.org/10.1007/978-3-319-67471-1_19
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