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Efficient attractor analysis based on self-dependent subsets of elements--an application to signal transduction
M Cárdenas-García1, J Lagunez-Otero, N Korneev
1Instituto de Quimica, UNAM, Ciudad Universitaria, Coyoacán, México. maura@servidor.unam.mx
Proceedings. International Conference on Intelligent Systems for Molecular Biology
|September 8, 2000
Summary
This study simplifies complex cell signaling networks, like the RAS/MAPK pathway, by identifying topological structures. This approach aids in predicting cellular responses and understanding oncogenesis.
Area of Science:
- Cellular Biology
- Systems Biology
- Computational Biology
Background:
- Signal transduction pathways transmit external signals via receptors, forming complex networks.
- The RAS/MAPK pathway is crucial in oncogenesis and cellular responses to stimuli.
Purpose of the Study:
- To analyze the topological structure within the RAS/MAPK signal transduction pathway.
- To develop a method for simplifying the analysis of complex biological networks.
Main Methods:
- Utilized a computer algorithm to identify topological structures in the RAS/MAPK pathway.
- Isolated smaller, independent subsets from the larger network and established their hierarchy.
Main Results:
- Demonstrated that interactions within the pathway induce a topological structure.
- Showed that this topological knowledge simplifies pathway analysis.
- Successfully isolated manageable subsets and built their hierarchy.
Conclusions:
- Network topology simplifies the analysis of signal transduction pathways.
- Subset identification facilitates the search for attractors in discrete dynamical systems.
- This approach aids in predicting the final states of elements in signaling pathways, with implications for understanding oncogenesis.