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Application of a novel and fast information-theoretic method to the discovery of higher-order correlations in protein
1Molecular Mining Corporation, Queen's University, Kingston, Ontario, Canada. steeg@qucis.queensu.ca
Abstract:
We present a fast, discrete data-mining approach to the problem of finding kappa-tuples of correlated amino acid residues in protein sequence data. When sets of sequence-distant sites display high mutual information, they may bespeak important structural or functional features. Our novel methodology overcomes the limitations of previous methods which examined only single-residue features or pairwise interactions.