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Improving Boolean Networks to Model Signaling Pathways. Bree Aldridge Diana Chai BE.400 Term Project December 5, 2002. Outline. Motivation / Project Goals Introduction to Model System Implementation: Boolean network Fuzzy network Results / Conclusions Future Work. Motivation.
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Improving Boolean Networks to Model Signaling Pathways Bree Aldridge Diana Chai BE.400 Term Project December 5, 2002
Outline • Motivation / Project Goals • Introduction to Model System • Implementation: • Boolean network • Fuzzy network • Results / Conclusions • Future Work
Motivation • Cellular states control behavior • Quantitative signaling and state data difficult to obtain • Boolean-like networks: • Representative of how signaling networks process and transmit information • “Simpler” than solving a huge system of ODEs • Tool to explore subnetwork interactions (crosstalk) • Missing data holes may be filled in with intuition
Project Goals • Explore the use of Boolean-like networks to model signaling events • Determine level of abstraction to which Boolean-like networks are useful • Make qualitative predictions about important nodes in signaling pathways
Model System Fibronectin a5b1 Insulin Grb2 Insulin Receptor FAK/Src IRS1 Sos P13K Ras Akt/PKB Raf Mek Erk DNA Synthesis Asthagiri and Lauffenburger, 2001 Anabi et al., 2001
Transient Behavior Asthagiri and Lauffenburger, 2001
DNA Synthesis Asthagiri et.al., 2000
Fuzzified Model • Go to Simulink: • Introduction to fuzzy logic • Membership functions • Rule based logic • Show working model
Take-home Results • Fuzzy logic networks are capable of capturing qualitative features of signaling networks (e.g. crosstalk) • Easy to build despite lack of quantitative information • Good for testing hypotheses at higher level of abstraction than ODE-based models
Conclusions • Boolean Networks are NOT sufficient to capture complex behaviors of signalling networks where behavior is not ALL or NONE • Fuzzy Logic Networks are best used at the qualitative prediction level • Also good for exploring how subnetworks interact • Especially good for when data is lacking
Future Work • Explore the insulin signaling pathway • Explore different levels of crosstalk • Explore sensitivity by changing membership functions and weighting rules
References • Annabi, Gautier, and Baron, Fed. Eur. Biochem. Soc.,507, 247-252 (2001) • Assoian and Schwartz, Curr. Opin. Genet. Dev.11, 48-53 (2001) • Asthagiri and Lauffenburger, Biotechnol. Prog. 17, 227-239 (2001) • Asthagiri, Reinhart, Horwitz, and Lauffenburger, J. Cell Sci.,113, 4499-4510 (2000) • Asthagiri et.al., J. Biol. Chem.,274, 27119-27127 (1999) • Eliceiri, Circ. Res., 89, 1104-1110 (2001) • Giancotti and Ruoslahti, Science285, 1028-1032 (1999) • Guilherme , Torres, and Czech, J. Biol. Chem.,273, 22899-22903 (1998) • Huang and Ferrell, PNAS, 93, 10078-10083 (1996) • Huang and Ingber, Exper. Cell Res.261, 91-103 (2000) • Schwartz and Baron, Curr. Opin. Cell Biol.11, 197-202 (1999) • Vuori and Ruoslahti, Science266, 1576-1578 (1994)