Visual data mining of genomic databases by immersive graph-based exploration

Abstract

Biologists are leading current research on genome characterization (sequencing, alignment, transcription), providing a huge quantity of raw data about many genome organisms. Extracting knowledge from this raw data is an important process for biologists, using usually data mining approaches. However, it is difficult to deals with these genomic information using actual bioinformatics data mining tools, because data are heterogeneous, huge in quantity and geographically distributed. In this paper, we present a new approach between data mining and virtual reality visualization, called visual data mining. Indeed Virtual Reality becomes ripe, with efficient display devices and intuitive interaction in an immersive context. Moreover, biologists use to work with 3D representation of their molecules, but in a desktop context. We present a software solution, Genome3DExplorer, which addresses the problem of genomic data visualization, of scene management and interaction. This solution is based on a well-adapted graphical and interaction paradigm, where local and global topological characteristics of data are easily visible, on the contrary to traditional genomic database browsers, always focused on the zoom and details level.

Immersive Visual Data Mining Based on Super High Definition Image

“…And as for the interaction between human and computer, immersive virtual environment would be used to enable the user to operate the visualized data directly and to explore data space as first person experience. Ammoura (Ammoura, 2001), Wegman (Wegman, 2002) and Ferey (Ferey, 2005) discuss the effectiveness of immersive virtual environment in visual data mining.…”

An integrative approach for biological data mining and visualisation

“…This kind of approach would enable us to investigate how a small change at the molecular level affects the higher abstract level (e.g., tissue or organ level). Another appealing challenge would be to visualise biological networks in three dimensions (Changsu Lee and Park, 2002;Férey et al, 2005).…”

Damming the genomic data flood using a comprehensive analysis and storage data structure

“…The research possibilities provided by genome-wide analysis have created a data deluge reminiscent of Moore’s Law ( 1 ). In a single year, one massively parallel sequencing machine can produce nearly nine times the amount of data currently housed in the US Library of Congress ( 2–4 ).…”

“…Alternately, the use of databases has been hampered due to challenges in data loading time and performance. The development of new techniques and tools is therefore necessary, as historical solutions have been rendered impractical due to the extreme volume of data generated ( 2–4 ).…”