Stochastic process algebra model of amyloidogenic processing under the influence of SORLA
Date of Publication
2016
Document Type
Bachelor's Thesis
Degree Name
Bachelor of Science in Mathematics with specialization in Business Applications
Subject Categories
Algebra | Mathematics
College
College of Science
Department/Unit
Mathematics and Statistics
Thesis Adviser
Angelyn R. Lao
Abstract/Summary
Studies based on the amyloid hypothesis have shown that the proteolytic breakdown of amyloidogenic processing is the main pathology of Alzheimer's disease (AD). In this study, we focused on the effect of receptor SORLA, a 230 kDa type-1 transmembrane glycoprotein, after binding with the amyloid precursor protein (APP) in the Trans-Golgi Network (TGN). We built a Stochastic Process Algebra (SPA) model to capture receptor SORLA's behavior and understand its influence in the APP processing. Through SPA modeling approach, the amyloidogenic processing is modeled as concurrent systems in continuous time Markov chains. We fitted the simulations of our model to the data published by Schmidt and colleagues in 2012. We built a model that initially considers the amyloidogenic processing to occur only in the endosomes. Then, we extended it so that the amyloidogenic processing also occurs in the TGN. In our study, we are able to validate the hypothesis proposed in Willnow and Spoelgen's study that there might be an indirect interaction between SORLA and [3-secretase. This indirect interaction takes place when APP and the receptor SORLA reverses, the APP that unbinds with SORLA may be cleaved by the [3-secretase in the TGN. Our SPA model brought new insights about SORLA's effect on the amyloidogenic processing, particularly to [3-secretase in the TGN.
Abstract Format
html
Language
English
Format
Electronic
Accession Number
CDTU020958
Shelf Location
Archives, The Learning Commons, 12F, Henry Sy Sr. Hall
Physical Description
1 computer disc ; 4 3/4 in.
Keywords
Amyloid beta-protein precursor; Stochastic processes
Recommended Citation
Dela Cruz, M. A., & Tenio, G. C. (2016). Stochastic process algebra model of amyloidogenic processing under the influence of SORLA. Retrieved from https://animorepository.dlsu.edu.ph/etd_bachelors/13989
Embargo Period
5-11-2021