@inproceedings{c27f4c3f3ec642a888d70886cb280f93,
title = "Identifying conserved discriminative motifs",
abstract = "The identification of regulatory motifs underlying gene expression is a challenging problem, particularly in eukaryotes. An algorithm to identify statistically significant discriminative motifs that distinguish between gene expression clusters is presented. The predictive power of the identified motifs is assessed with a supervised Na{\"i}ve Bayes classifier. An information-theoretic feature selection criterion helps find the most informative motifs. Results on benchmark and real data demonstrate that our algorithm accurately identifies discriminative motifs. We show that the integration of comparative genomics information into the motif finding process significantly improves the discovery of discriminative motifs and overall classification accuracy.",
author = "Jyotsna Kasturi and Raj Acharya and Ross Hardison",
note = "Copyright: Copyright 2021 Elsevier B.V., All rights reserved.; 3rd IAPR International Conference on Pattern Recognition in Bioinformatics, PRIB 2008 ; Conference date: 15-10-2008 Through 17-10-2008",
year = "2008",
doi = "10.1007/978-3-540-88436-1\_29",
language = "English (US)",
isbn = "3540884343",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "334--348",
booktitle = "3rd IAPR International Conference on Pattern Recognition in Bioinformatics, PRIB 2008",
address = "Germany",
}