Abstract
Consensus and sequence pattern analysis on family alignments are extensively used to identify new family members and to determine functionally and structurally important identities. Since these common approaches emphasize dominant characteristics of the family and assume residue identities are independent at each position, there is no way to describe residue preferences outside of the family consensus. In this study, we propose a novel approach to detect motifs outside the consensus of a protein family alignment via an information theoretic approach. We implemented an algorithm that discovers frequent residue motifs that are high in information content and outside of the family consensus, called informative motifs, inspired by the classic Apriori algorithm. We observed that these informative motifs are mostly spatially localized and present distinctive features of various members of the family. Availability: The source code is available upon request from the authors.
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Ozer, H.G., Ray, W.C. (2007). Informative Motifs in Protein Family Alignments. In: Giancarlo, R., Hannenhalli, S. (eds) Algorithms in Bioinformatics. WABI 2007. Lecture Notes in Computer Science(), vol 4645. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74126-8_15
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DOI: https://doi.org/10.1007/978-3-540-74126-8_15
Publisher Name: Springer, Berlin, Heidelberg
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