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- W2065288977 abstract "In recent years, sequence database searching has been conducted through local alignment heuristics, pattern-matching, and comparison of short statistically significant patterns. While these approaches have unlocked many clues as to sequence relationships, they are limited in that they do not provide context-sensitive searching capabilities (e.g. considering pseudoknots, protein binding positions, and complementary base pairs). Stochastic grammars (hidden Markov models HMMs and stochastic context-free grammars SCFG) do allow for flexibility in terms of local context, but the context comes at the cost of increased computational complexity. In this paper we introduce a new grammar based method for searching for RNA motifs that exist within a conserved RNA structure. Our method constrains computational complexity by using a chain of topology elements. Through the use of a case study we present the algorithmic approach and benchmark our approach against traditional methods." @default.
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- W2065288977 date "2007-09-01" @default.
- W2065288977 modified "2023-10-18" @default.
- W2065288977 title "A GRAMMAR BASED METHODOLOGY FOR STRUCTURAL MOTIF FINDING IN ncRNA DATABASE SEARCH" @default.
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- W2065288977 doi "https://doi.org/10.1142/9781860948732_0024" @default.
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