The Effects of Ordered-Series-of-Motifs Anchoring and Sub-Class Modeling on the Generation of HMMs Representing Highly Divergent Protein Sequences
نویسندگان
چکیده
Hidden Markov Models (HMMs) provide a flexible method for representing protein sequence data. Highly divergent data require a more complex approach to HMM generation than previously demonstrated. We describe a strategy of motif anchoring and sub-class modeling that aids in the construction of more informative HMMs as determined by a new algorithm called a stability measure.
منابع مشابه
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عنوان ژورنال:
- Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
دوره شماره
صفحات -
تاریخ انتشار 1999