Publication Date
Fall 2023
Degree Type
Master's Project
Degree Name
Master of Science in Bioinformatics (MSBI)
Department
Computer Science
First Advisor
Leonard Wesley
Second Advisor
William Andreopoulos
Third Advisor
Cleber Ouverney
Keywords
Alzheimer’s Disease, Mild Cognitive Impairment, Epigenetics, Modeller, SNP
Abstract
In the population of adult human patients who over express Beta and Tau Amyloids, it is unclear why 40% of them do not have Alzheimer’s Disease (AD), when all patients with AD have an overexpression of Beta and Tau Amyloids. The MCI-AD-DTI project’s epigenetic pipeline is an evolving computation tool that seeks epigenetic-related information related to the observed disparity. The MCI-AD-DTI’s epigenetic pipeline’s ability to identify mutations currently relies solely on PyPDB for verification of its protein functionality evaluation. The assessment process of the industry standard application, Modeller10.4, is independent from the current epigenetic pipeline’s protein evaluation algorithm. Thus, this project concludes that integrating Modeller10.4, with its protein modeling, would contribute through an increase in the ability to distinguish between which Single Nucleotide Polymorphic (SNP) mutations change functionality.
Recommended Citation
Jacobson, Grant Galileo, "Mild Cognitive Impairment and Alzheimer’s Disease Detection and Testing Interface (MCI-ADDTI) Modeller10.4 Integrating Structure-Function Prediction Modules" (2023). Master's Projects. 1333.
DOI: https://doi.org/10.31979/etd.b4cn-37w6
https://scholarworks.sjsu.edu/etd_projects/1333
