PLC-gamma pathway component of the Bhalla-Iyengar model

Model Status

This particular version of the CellML model describes the PLC-gamma pathway component of the Bhalla-Iyengar model. This model is able to be solved but does not give the correct results as it is not connected to the other modules of the pathway. ValidateCellML verifies this model as valid CellML but detects unit inconsistencies.

Model Structure

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 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. Feedback can result in bistable behavior with discrete steady-state activities, well-defined input thresholds for transition between states and prolonged signal output, and signal modulation in response to transient stimuli. 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.

The original paper reference is cited below:

Emergent properties of networks of biological signaling pathways. Bhalla US, Iyengar R. Science 1999 Jan 15; 283(5400); 381-7. PubMed ID: 9888852

A rendering of the PLC gamma pathway component of the Bhalla-Iyengar model.