From 6782abf56c5b8aebae2dad222e98426b67a21c00 Mon Sep 17 00:00:00 2001 From: Laura Masa Date: Tue, 9 Jul 2024 16:01:55 +0000 Subject: [PATCH] Update README.md --- README.md | 22 ++++++++++++++++++---- 1 file changed, 18 insertions(+), 4 deletions(-) diff --git a/README.md b/README.md index b2fa2f6..13c62cc 100644 --- a/README.md +++ b/README.md @@ -1,9 +1,23 @@ -This repository documents the work conducted for my master’s thesis titled "Analyzing Gene Expression Datasets for Disease Annotation Modeling." +Author: Laura Masa Martínez +This repository documents the work conducted for my master’s thesis titled "Analyzing Gene Expression Datasets for Disease Annotation Modeling" + +**Objectives** 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. +1. Differential Gene Expression Analysis: To create a Personalized Perturbation Profile (PEEP) that captures gene expression variations for individual and group-level comparisons. +2. Advancing Personalized Medicine: To leverage PEEP profiles for discovering tailored therapeutic interventions and exploring opportunities for drug repositioning for novel therapeutic applications. +3. Modeling Disease-Gene Associations: To enhance the semantic understanding and predictive accuracy of gene-disease relationships through advanced modeling techniques. + + +**Folders structure** + +| Folder | Content | +| ------ | ------ | +| data_processing | Code and datasets associated with the initial phase of the project. It includes resources for **collecting gene expression data**, **preprocessing the data**, and **selecting relevant subsets** for subsequent analysis. | +| data_analysis | Code, data, and figures used for the **analysis and visualization of gene expression data**. This includes performing **differential gene expression analysis**, generating descriptive statistics, and visualizing the results of both group-wise and individual-level gene regulation studies. | +| analysis_drug_repurposing | Code and data used for analyzing drug-target relationships and visualizing potential treatments based on the findings from the gene-disease association data. | + + -- 2.24.1