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Automatic Pattern Embedding in Protein Structure Models
November/December 2001 (vol. 16 no. 6)
pp. 21-25

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.

Jadwiga Bienkowska, Hongxian He, Temple F. Smith, "Automatic Pattern Embedding in Protein Structure Models," IEEE Intelligent Systems, vol. 16, no. 6, pp. 21-25, Nov.-Dec. 2001, doi:10.1109/5254.972074
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