Elements of information theory
Elements of information theory
RECOMB '01 Proceedings of the fifth annual international conference on Computational biology
Machine Learning
From promoter sequence to expression: a probabilistic framework
Proceedings of the sixth annual international conference on Computational biology
Combining phylogenetic and hidden Markov models in biosequence analysis
RECOMB '03 Proceedings of the seventh annual international conference on Research in computational molecular biology
Finding Regulatory Elements Using Joint Likelihoods for Sequence and Expression Profile Data
Proceedings of the Eighth International Conference on Intelligent Systems for Molecular Biology
An Exact Algorithm to Identify Motifs in Orthologous Sequences from Multiple Species
Proceedings of the Eighth International Conference on Intelligent Systems for Molecular Biology
A Statistical Method for Finding Transcription Factor Binding Sites
Proceedings of the Eighth International Conference on Intelligent Systems for Molecular Biology
Clustering of diverse genomic data using information fusion
Proceedings of the 2004 ACM symposium on Applied computing
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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 Naïve 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.