Biochemical signaling networks were constructed with experimentally obtained constants and analyzed by computational methods to understand their role in complex biological processes. These networks exhibit emergent properties such as integration of signals across multiple time scales, generation of distinct outputs depending on input strength and duration, and self-sustaining feedback loops. Properties of signaling networks raise the possibility that information for "learned behavior" of biological systems may be stored within intracellular biochemical reactions that comprise signaling pathways.
Model Type: Neuron or other electrically excitable cell; Molecular Network
Cell Type(s): Hippocampus CA1 pyramidal GLU cell
Currents: I Calcium
Transmitters: Glutamate
Model Concept(s): Temporal Pattern Generation; Detailed Neuronal Models; Short-term Synaptic Plasticity; Signaling pathways
Simulation Environment: GENESIS (web link to model)
Implementer(s): Bhalla, Upinder S [bhalla at ncbs.res.in]
References:
Bhalla US, Iyengar R. (1999). Emergent properties of networks of biological signaling pathways. Science (New York, N.Y.). 283 [PubMed]