The relationship between the family SH of simple splicing languages, which was recently introduced by A. Mateescu and coauthors, and the family SLT of strictly locally testable languages is clarified by establishing an ascending hierarchy of families fS i H : i \Gamma1g of splicing languages for which SH = S1H and the union of the families is the family SLT . A procedure is given which, for an arbitrary regular language L, determines whether L is in SLT and, when L is in SLT , specifies constructively the smallest family in the hierarchy to which L belongs. Examples are given of sets of restriction enzymes for which the action on DNA molecules is naturally represented by splicing systems of the types discussed. Key words. Splicing systems, H Systems, DNA Computing, local testability, regular languages, restriction enzymes 1 Introduction The splicing system concept was introduced in [6] as a formal device for the generation of languages and as a formal model of specific forms ...

Summary. We consider the result of a wet splicing procedure after the reaction has run to its completion, or limit, and we try to describe the molecules that will be present at this final stage. In language theoretic terms the splicing procedure is modeled as an H system, and the molecules that we want to consider correspond to a subset of the splicing language which we call the limit language. We give a number of examples, including one based on differential equations, and we propose a definition for the limit language. With this definition we prove that a language is regular if and only if it is the limit language of a reflexive and symmetric splicing system. 1

Grammatical Inference is the problem of learning a formal grammar that characterizes a set of strings over an alphabet. In particular, the problem of inferring regular grammars from positive data is considered in this paper. In the framework of identification in the limit, subfamilies of the family of regular languages have been defined in the literature. These include Strictly Locally Testable Languages(SLT) and Terminal Distinguishable Regular Languages (TDRL). TDRL's have been shown to possess many desirable properties for inference. SLT languages have been applied to protein sequence analysis. When dealing with biological sequences, local alignment issues become important. In this paper, a framework has been proposed for introducing local alignment considerations into grammar inference models and a learning algorithm has been given for a family defined as Locally Aligned TDRL. Results of application of the algorithm to protein sequence data and comparison with SLT are presented. Experimentally, it is inferred that the generalization of LA-TDRL is not affected by noise that is present in the data and the amount of generalization can be controlled by an input parameter.

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The main concept of molecular computing depends on DNA self-assembly abilities and on modifying DNA with the help of enzymes during genetic operations. In the typical DNA computing a sequence of operations executed on DNA strings in parallel is called an algorithm, which is also determined by a model of DNA strings. This methodology is similar to the soft hardware specialized architecture driven here by heating, cooling and enzymes, especially polymerases used for copying strings. As it is described in this paper the polymerase Taq properties are changed by modifying its DNA sequence in such a way that polymerase side activities together with peptide chains, responsible for destroying amplified strings, are cut off. Thus, it introduces the next level of molecular computing. The genetic operation execution succession and the given molecule model with designed nucleotide sequences produce computation results and additionally they modify enzymes, which directly influence on the computation process. The information flow begins to circulate. Additionally, such optimized enzymes are more suitable for nanoconstruction, because they have only desired characteristics. The experiment was proposed to confirm the possibilities of the suggested implementation.