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ABSTRACT
<p>This article describes an implementation of a set of rules for automatically embedding a minimal functional sequence pattern in a structural hidden Markov model. An HMM is constructed from the atomic coordinates of a protein structure deposited in the PDB (protein databank) by an entirely automated procedure. This procedure generates a set of HMMs that represent distinct three-dimensional folds of protein structures. The next step generates a sequence pattern for the functional family from a set of homologous sequences. The strictly conserved positions from the pattern are selected for embedding in each structural HMM. The final product is a library of wide-ranging fold models with encoded information about the functional families. This library is used to assign the fold models to protein sequences.</p>
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CITATION
Jadwiga Bienkowska, Temple F. Smith, Hongxian He, "Automatic Pattern Embedding in Protein Structure Models", IEEE Intelligent Systems, vol. 16, no. , pp. 21-25, November/December 2001, doi:10.1109/5254.972074
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