Spatial data mining is a process used to discover interesting but not explicitly available, highly usable patterns embedded in both spatial and nonspatial data, which are possibly ...
Background: Recent advances with high-throughput methods in life-science research have increased the need for automatized data analysis and visual exploration techniques. Sophisti...
Time-series data is a common target for visual analytics, as they appear in a wide range of application domains. Typical tasks in analyzing time-series data include identifying cy...
We will try to address the need for a formal foundation for visualization by taking an analytic approach to defining D. Since an arbitrary function D: U V will not produce display...
William L. Hibbard, Charles R. Dyer, Brian E. Paul
Background: Analysis of data from high-throughput experiments depends on the availability of well-structured data that describe the assayed biomolecules. Procedures for obtaining ...