Title :
MedVir: 3D visual interface applied to gene profile analysis
Author_Institution :
Dept. de Arquitectura y Tecnol. de Sist. Informaticos, Univ. Politec. de Madrid, Madrid, Spain
Abstract :
The use of data mining techniques for the gene profile discovery of diseases, such as cancer, is becoming usual in many researches. These techniques do not usually analyze the relationships between genes in depth, depending on the different variety of manifestations of the disease (related to patients). This kind of analysis takes a considerable amount of time and is not always the focus of the research. However, it is crucial in order to generate personalized treatments to fight the disease. Thus, this research focuses on finding a mechanism for gene profile analysis to be used by the medical and biologist experts. In this research, the MedVir framework is proposed. It is an intuitive mechanism based on the visualization of medical data such as gene profiles, patients, clinical data, etc. MedVir, which is based on an Evolutionary Optimization technique, is a Dimensionality Reduction (DR) approach that presents the data in a three dimensional space. Furthermore, thanks to Virtual Reality technology, MedVir allows the expert to interact with the data in order to tailor it to the experience and knowledge of the expert.
Keywords :
biology computing; cancer; data mining; data visualisation; evolutionary computation; optimisation; user interfaces; virtual reality; 3D visual interface; DR approach; MedVir framework; cancer; data mining techniques; dimensionality reduction approach; diseases; evolutionary optimization technique; gene profile analysis; gene profile discovery; medical data visualization; virtual reality technology; Bioinformatics; Biology; Data visualization; Diseases; Optimization; Virtual reality; Visualization; DNA microarray; dimensionality reduction; manifold learning; visualization;
Conference_Titel :
High Performance Computing and Simulation (HPCS), 2012 International Conference on
Conference_Location :
Madrid
Print_ISBN :
978-1-4673-2359-8
DOI :
10.1109/HPCSim.2012.6266996