This repository documents the work conducted for my master’s thesis titled "Analyzing Gene Expression Datasets for Disease Annotation Modeling."
The principal objective of this thesis was to design and implement an automated system for the extraction, processing, and analysis of gene-disease association data. This system was developed to generate a detailed gene-disease annotation model, including gene identifiers, gene expression profiles, and comprehensive metadata. The automation of these processes was intended to provide a structured and efficient platform to support biomedical research efforts and the identification of novel therapeutic targets.
In addition to the main objective, the thesis aimed to achieve several secondary goals:
Differential Gene Expression Analysis: To create a Personalized Perturbation Profile (PEEP) that captures gene expression variations for individual and group-level comparisons.
Advancing Personalized Medicine: To leverage PEEP profiles for discovering tailored therapeutic interventions and exploring opportunities for drug repositioning for novel therapeutic applications.
Modeling Disease-Gene Associations: To enhance the semantic understanding and predictive accuracy of gene-disease relationships through advanced modeling techniques.
