Emergent Properties of Networks of Biological Signaling Pathways
(Science, 283:381-387 1999).
Authors:

Upinder S. Bhalla: National Centre for Biological Sciences

Ravi Iyengar: Mount Sinai School of Medicine

• Constants and database of references
• Downloading GENESIS and Kinetikit.
• Example of model construction for Protein Kinase C (PKC)
• Discussion of models: Accuracy, robustness and diffusion.
• Simulation details for figures in the paper

Abstract

Many distinct signaling pathways allow the cell to receive, process and respond to information. Often, components of different pathways interact, resulting in signaling networks. Biochemical signaling networks were constructed using 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. Feedback can result in bistable behavior with discrete steady-state activities and well-defined input thresholds for transition between states, and prolonged signal output and signal modulation in response to transient stmuli. These 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.