A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2013; you can also visit the original URL.
The file type is
Motivation: The huge growth in gene expression data calls for the implementation of automatic tools for data processing and interpretation. Results: We present a new and comprehensive machine learning data mining framework consisting in a non-linear PCA neural network for feature extraction, and probabilistic principal surfaces combined with an agglomerative approach based on Negentropy aimed at clustering gene microarray data. The method, which provides a user-friendly visualization interface,doi:10.1093/bioinformatics/btk026 pmid:16397005 fatcat:vtlz2pqozfa7jacuqyr5uaggm4