基于沉浸式图探索的基因组数据库可视化数据挖掘
Visual Data Mining of Genomic Databases by Immersive Graph-Based Exploration
摘要：
生物学家正在领导当前的基因组表征研究（测序，比对，转录），提供了大量关于许多基因组生物的原始数据。从这些原始数据中提取知识是生物学家的一个重要过程，通常使用数据挖掘方法。然而，由于这些基因组信息的异构性、海量性和地理分布性，使得现有的生物信息学数据挖掘工具难以处理这些信息。在本文中，我们提出了一种新的方法之间的数据挖掘和虚拟现实可视化，称为可视化数据挖掘。事实上，虚拟现实已经成熟，在沉浸式环境中具有高效的显示设备和直观的交互。此外，生物学家使用3D表示他们的分子，但在桌面环境中。我们提出了一个软件解决方案，基因组3DExplorer，它解决了基因组数据可视化的问题，场景管理和交互。这种解决方案是基于一个适应良好的图形和交互范例，其中数据的局部和全局拓扑特征是很容易看到的，相反，传统的基因组数据库浏览器，总是集中在缩放和细节水平。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
