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-Work created by Laura Masa
+This repository documents the work conducted for my master’s thesis titled "Analyzing Gene Expression Datasets for Disease Annotation Modeling."
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+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.
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+In addition to the main objective, the thesis aimed to achieve several secondary goals:
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+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.