MOTIVATION: This application aims at assisting researchers with the extraction of significant medical and biological knowledge from data sets with complex relationships among their variables. RESULTS: Non-hypothesis-driven approaches like Principal Curves of Oriented Points (PCOP) are a very suitable method for this objective. PCOP allows for obtaining of a representative pattern from a huge quantity of data of independent variables in a very flexible and direct way. A web server has been designed to automatically realize 'non-linear pattern' analysis, 'hidden-variable-dependent' clustering, and new samples 'local-dispersion-dependent' classification from the data involving new statistical techniques using the PCOP calculus. The tools facilitate the managing, comparison and visualization of results in a user-friendly graphical interface. AVAILABILITY: http://ibb.uab.es/revresearch.
MOTIVATION: This application aims at assisting researchers with the extraction of significant medical and biological knowledge from data sets with complex relationships among their variables. RESULTS: Non-hypothesis-driven approaches like Principal Curves of Oriented Points (PCOP) are a very suitable method for this objective. PCOP allows for obtaining of a representative pattern from a huge quantity of data of independent variables in a very flexible and direct way. A web server has been designed to automatically realize 'non-linear pattern' analysis, 'hidden-variable-dependent' clustering, and new samples 'local-dispersion-dependent' classification from the data involving new statistical techniques using the PCOP calculus. The tools facilitate the managing, comparison and visualization of results in a user-friendly graphical interface. AVAILABILITY: http://ibb.uab.es/revresearch.