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Quantification of information transfer via cellular signal transduction pathways
B N Kholodenko1, J B Hoek, H V Westerhoff
1Department of Pathology, Anatomy and Cell Biology, Thomas Jefferson University, Philadelphia, PA 19107, USA. kholode1@jeflin.tju.edu
FEBS Letters
|October 7, 1997
Summary
Signal transfer analysis quantifies cellular signaling sensitivity using response coefficients. This framework reveals how cascade depth and independent pathways impact signal propagation and cellular information transfer.
Area of Science:
- Systems Biology
- Cellular Signaling
- Quantitative Biology
Background:
- Cellular signal transduction pathways are complex information processing systems.
- Quantitative analysis of signal transfer is crucial for understanding cellular responses.
- Existing formalisms for metabolic networks offer a basis for analyzing signaling pathways.
Purpose of the Study:
- Develop a quantitative framework for analyzing signal transfer in cellular signaling networks.
- Define and utilize response coefficients to measure signal transduction sensitivity.
- Investigate how network structure influences signal propagation and amplification.
Main Methods:
- Introduced Signal Transfer Analysis (STA) based on metabolic network formalisms.
- Defined response coefficient as fractional change in target activity per fractional signal change.
- Analyzed idealized signaling cascades, branched pathways, and networks with feedback.
Main Results:
- For cascades without feedback, total response is the product of local response coefficients.
- Demonstrated conditions under which increased cascade levels enhance target sensitivity.
- Showed independent contribution of parallel pathways to total response in the absence of feedback.
Conclusions:
- Signal Transfer Analysis provides a general method for quantifying cellular information transfer.
- The framework highlights key differences between signaling and metabolic networks.
- This approach enables a deeper understanding of signal amplification and integration in biological systems.