Open Access Research article

Multi-compartmental modeling of SORLA’s influence on amyloidogenic processing in Alzheimer’s disease

Angelyn Lao1, Vanessa Schmidt2, Yvonne Schmitz1, Thomas E Willnow2* and Olaf Wolkenhauer13*

Author Affiliations

1 Department of Systems Biology and Bioinformatics, Institute of Computer Science, University of Rostock, Ulmenstrasse 69, Rostock, 18057, Germany

2 Max-Delbrück-Center for Molecular Medicine, Robert-Roessle-Str. 10, Berlin, D-13125, Germany

3 Stellenbosch Institute for Advanced Study (STIAS), Stellenbosch, 7600, South Africa

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BMC Systems Biology 2012, 6:74  doi:10.1186/1752-0509-6-74

Published: 22 June 2012

Additional files

Additional file 1:

Mathematical Modeling. The complete formulation of the model, realized as set of ODEs. Table S1 – Variables in the biochemical network. The table contains the description of the variables that are used in the different compartments of the biochemical network (shown in Figure 1). Table S2 – Variables and parameters in the mathematical model. The table contains the unit and the description of the variables and parameters used in the mathematical model. Table S3 – Simulation steps. The steps performed for the estimation of parameter values are elaborated here. Table S4 - Estimated parameter values for Figure2. The table shows a set of estimated parameter values, which has the lowest residual value out of 500 simulation runs. Figure S1 – Concentration values of the secretases with higher SORLATotvalues. The figure shows simulations of the influence of intermediate levels of SORLA that are greater that the value of SORLATot, on the amount of α-secretase and β-secretase concentrations on APP processing.

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