Correlative visualizaton techniques for multidimensional data

High Performance Visualizaton

Top-k Correlative Graph Mining

Correlation mining has been widely studied due to its ability for discovering the underlying occurrence dependency between objects. However, correlation mining in graph databases is expensive due to the complexity of graph data. In this paper, we study the problem of mining top-k correlative subgraphs in the database, which share similar occurrence distributions with a given query graph. The se...

A combined method for correlative 3D imaging of biological samples from macro to nano scale

Correlative analysis requires examination of a specimen from macro to nano scale as well as applicability of analytical methods ranging from morphological to molecular. Accomplishing this with one and the same sample is laborious at best, due to deformation and biodegradation during measurements or intermediary preparation steps. Furthermore, data alignment using differing imaging techniques tu...

A need for a 'whole-istic functional genomics' approach in complex human diseases: arthritis

'Genomic tools', such as gene/protein chips, single nucleotide polymorphism and haplotype analyses, are empowering us to generate staggering amounts of correlative data, from human/animal genetics and from normal and disease-affected tissues obtained from complex diseases such as arthritis. These tools are transforming molecular biology into a 'data rich' science, with subjects with an '-omic' ...

Correlative Light Electron Microscopy: Connecting Synaptic Structure and Function

Many core paradigms of contemporary neuroscience are based on information obtained by electron or light microscopy. Intriguingly, these two imaging techniques are often viewed as complementary, yet separate entities. Recent technological advancements in microscopy techniques, labeling tools, and fixation or preparation procedures have fueled the development of a series of hybrid approaches that...