Artificial intelligence and molecular biology
Artificial intelligence and molecular biology
The computational linguistics of biological sequences
Artificial intelligence and molecular biology
Fixed Point Languages, Equality Languages, and Representation of Recursively Enumerable Languages
Journal of the ACM (JACM)
Introduction To Automata Theory, Languages, And Computation
Introduction To Automata Theory, Languages, And Computation
Some computational properties of Tree Adjoining Grammars
ACL '85 Proceedings of the 23rd annual meeting on Association for Computational Linguistics
Journal of Computer and System Sciences
Operations and language generating devices suggested by the genome evolution
Theoretical Computer Science
On some operations on strings suggested by gene assembly in ciliates
New Generation Computing
Recombination Patterns for Natural Syntax
IWINAC '09 Proceedings of the 3rd International Work-Conference on The Interplay Between Natural and Artificial Computation: Part I: Methods and Models in Artificial and Natural Computation. A Homage to Professor Mira's Scientific Legacy
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The authors are concerned with analysing formal linguistic properties of DNA sequences in which a number of the language theoretic analysis on DNA sequences are established by means of computational methods. First, employing a formal language theoretic framework, the authors consider a kind of evolutionary problem of DNA sequences, asking (1) how DNA sequences were initially created and then evolved (grew up) to be a language of certain complexity, and (2) what primitive constructs were minimally required for the process of evolution. In terms of formal linguistic concepts, the authors present several results that provide their views on these questions at a conceptual level. Based on the formal analysis on these biological questions, the authors then choose a certain type of tree generating grammars called tree adjunct grammars (TAG) to attach the problem of modeling the secondary structure of RNA sequences. By proposing an extended model of TAGs, the authors demonstrate the usefulness of the grammars for modeling some typical RNA secondary structures including "pseudoknots", which suggests that TAG families as RNA grammars have a great potential for RNA secondary structure prediction.