@inproceedings{ae7a9b0328354672ae7a63216631bead,
title = "Analysis of tiling microarray data by learning vector quantization and relevance learning",
abstract = "We apply learning vector quantization to the analysis of tiling microarray data. As an example we consider the classification of C. elegans genomic probes as intronic or exonic. Training is based on the current annotation of the genome. Relevance learning techniques are used to weight and select features according to their importance for the classification. Among other findings, the analysis suggests that correlations between the perfect match intensity of a particular probe and its neighbors are highly relevant for successful exon identification.",
keywords = "GENOME",
author = "Michael Biehl and Rainer Breitling and Yang Li",
note = "Relation: http://www.rug.nl/gbb/ date_submitted:2009 Rights: University of Groningen, Groningen Biomolecular Sciences and Biotechnology Institute; 8th International Conference on Intelligent Data Engineering and Automated Learning ; Conference date: 16-12-2007 Through 19-12-2007",
year = "2007",
doi = "10.1007/978-3-540-77226-2_88",
language = "English",
isbn = "978-3-540-77225-5",
series = "LECTURE NOTES IN COMPUTER SCIENCE",
publisher = "Springer",
pages = "880--889",
editor = "H Yin and P Tino and E Corchado and W Byrne and Yao",
booktitle = "INTELLIGENT DATA ENGINEERING AND AUTOMATED LEARNING - IDEAL 2007",
}