PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

A web server for automatic analysis and extraction of relevant biological knowledge
J. Cedano, M. Huerta, I. Estrada, F. Ballllosera, O. Conchillo, Pedro Delicado and E. Querol
Computers in Biology and Medicine Volume 37, Number 11, pp. 1672-1675, 2007. ISSN 0010-4825

Abstract

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

EPrint Type:Article
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Computational, Information-Theoretic Learning with Statistics
ID Code:3405
Deposited By:Pedro Delicado
Deposited On:10 February 2008