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: A method to evaluate and analyze the massive data generated by series of microarray experiments is of utmost importance to reveal the hidden patterns of gene expressio...
Junbai Wang, Jan Delabie, Hans Christian Aasheim, ...
Many real life problems require the classification of items into naturally ordered classes. These problems are traditionally handled by conventional methods intended for the class...
: Extraction of meaningful information from large experimental datasets is a key element of bioinformatics research. One of the challenges is to identify genomic markers in Hepatit...
Kwong-Sak Leung, Kin-Hong Lee, Jin Feng Wang, Eddi...
The analysis of texture is an important subroutine in application areas as diverse as biology, medicine, robotics, and forensic science. While the last three decades have seen ext...