Transformation of Attributed Structures with Cloning (Long Version)

Copying, or cloning, is a basic operation used in the specification of many applications in computer science. However, when dealing with complex structures, like graphs, cloning is not a straightforward operation since a copy of a single vertex may involve (implicitly)copying many edges. Therefore, most graph transformation approaches forbid the possibility of cloning. We tackle this problem by providing a framework for graph transformations with cloning. We use attributed graphs and allow rules to change attributes. These two features (cloning/changing attributes) together give rise to a powerful formal specification approach. In order to handle different kinds of graphs and attributes, we first define the notion of attributed structures in an abstract way. Then we generalise the sesqui-pushout approach of graph transformation in the proposed general framework and give appropriate conditions under which attributed structures can be transformed. Finally, we instantiate our general framework with different examples, showing that many structures can be handled and that the proposed framework allows one to specify complex operations in a natural way

Composition of M,N-adhesive Categories with Application to Attribution of Graphs

This paper continues the work on M,N-adhesive categories and shows some important composition properties for these categories. We present a new concept of attributed graphs and show that the corresponding category is M,N-adhesive. As a consequence, we inherit all nice properties for M,N-adhesive systems such as the Local Church-Rosser Theorem, the Parallelism Theorem, and the Concurrency Theorem for this type of attributed graphs

A Unifying Theory for Graph Transformation

The field of graph transformation studies the rule-based transformation of graphs. An important branch is the algebraic graph transformation tradition, in which approaches are defined and studied using the language of category theory. Most algebraic graph transformation approaches (such as DPO, SPO, SqPO, and AGREE) are opinionated about the local contexts that are allowed around matches for rules, and about how replacement in context should work exactly. The approaches also differ considerably in their underlying formal theories and their general expressiveness (e.g., not all frameworks allow duplication). This dissertation proposes an expressive algebraic graph transformation approach, called PBPO+, which is an adaptation of PBPO by Corradini et al. The central contribution is a proof that PBPO+ subsumes (under mild restrictions) DPO, SqPO, AGREE, and PBPO in the important categorical setting of quasitoposes. This result allows for a more unified study of graph transformation metatheory, methods, and tools. A concrete example of this is found in the second major contribution of this dissertation: a graph transformation termination method for PBPO+, based on decreasing interpretations, and defined for general categories. By applying the proposed encodings into PBPO+, this method can also be applied for DPO, SqPO, AGREE, and PBPO

Circuit Width Estimation via Effect Typing and Linear Dependency (Long Version)

Circuit description languages are a class of quantum programming languages in which programs are classical and produce a description of a quantum computation, in the form of a quantum circuit. Since these programs can leverage all the expressive power of high-level classical languages, circuit description languages have been successfully used to describe complex and practical quantum algorithms, whose circuits, however, may involve many more qubits and gate applications than current quantum architectures can actually muster. In this paper, we present Proto-Quipper-R, a circuit description language endowed with a linear dependent type-and-effect system capable of deriving parametric upper bounds on the width of the circuits produced by a program. We prove both the standard type safety results and that the resulting resource analysis is correct with respect to a big-step operational semantics. We also show that our approach is expressive enough to verify realistic quantum algorithms.Comment: 21 pages (excluding references), 21 figure

Detection of the TCDD binding-fingerprint within the Ah receptor ligand binding domain by structurally driven mutagenesis and functional analysis

The aryl hydrocarbon receptor (AhR) is a ligand-dependent, basic helix-loop-helix Per-Arnt-Sim (PAS)-containing transcription factor that can bind and be activated by structurally diverse chemicals, including the toxic environmental contaminant 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD). Our previous three-dimensional homology model of the mouse AhR (mAhR) PAS B ligand binding domain allowed identification of the binding site and its experimental validation. We have extended this analysis by conducting comparative structural modeling studies of the ligand binding domains of six additional highaffinity mammalian AhRs. These results, coupled with site-directed mutagenesis and AhR functional analysis, have allowed detection of the "TCDD binding-fingerprint" of conserved residues within the ligand binding cavity necessary for high-affinity TCDD binding and TCDD-dependent AhR transformation DNA binding. The essential role of selected residues was further evaluated using molecular docking simulations of TCDD with both wild-type and mutant mAhRs. Taken together, our results dramatically improve our understanding of the molecular determinants of TCDD binding and provide a basis for future studies directed toward rationalizing the observed species differences in AhR sensitivity to TCDD and understanding the mechanistic basis for the dramatic diversity in AhR ligand structure. © 2009 American Chemical Society

Utilization of tmRNA sequences for bacterial identification

In recent years, molecular approaches based on nucleotide sequences of ribosomal RNA (rRNA) have become widely used tools for identification of bacteria [1-4]. The high degree of evolutionary conservation makes 16S and 23S rRNA molecules very suitable for phylogenetic studies above the species level [3-5]. More than 16,000 sequences of 16S rRNA are presently available in public databases [4,6]. The 16S rRNA sequences are commonly used to design fluorescently labeled oligonucleotide probes. Fluorescence in situ hybridization (FISH) with these probes followed by observation with epifluorescence microscopy allows the identification of a specific microorganism in a mixture with other bacteria [2-4]. By shifting probe target sites from conservative to increasingly variable regions of rRNA, it is possible to adjust the probe specificity from kingdom to species level. Nevertheless, 16S rRNA sequences of closely related strains, subspecies, or even of different species are often identical and therefore can not be used as differentiating markers [3]. Another restriction concerns the accessibility of target sites to the probe in FISH experiments. The presence of secondary structures, or protection of rRNA segments by ribosomal proteins in fixed cells can limit the choice of variable regions as in situ targets for oligonucleotide probes [7,8]. One way to overcome the limitations of in situ identification of bacteria is to use molecules other than rRNA for phylogenetic identification of bacteria, for which nucleotide sequences would be sufficiently divergent to design species specific probes, and which would be more accessible to oligonucleotide probes. For this purpose we investigated the possibility of using tmRNA (also known as 10Sa RNA; [9-11]). This molecule was discovered in E. coli and described as small stable RNA, present at ~1,000 copies per cell [9,11]. The high copy number is an important prerequisite for FISH, which works best with naturally amplified target molecules. In E. coli, tmRNA is encoded by the ssrA gene, is 363 nucleotides long and has properties of tRNA and mRNA [12,13]. tmRNA was shown to be involved in the degradation of truncated proteins: the tmRNA associates with ribosomes stalled on mRNAs lacking stop codons, finally resulting in the addition of a C-terminal peptide tag to the truncated protein. The peptide tag directs the abnormal protein to proteolysis [14,15]. 165 tmRNA sequences have so far (August 2001; The tmRNA Website: http://www.indiana.edu/~tmrna/) been determined [16,17]. The tmRNA is likely to be present in all bacteria and has also been found in algae chloroplasts, the cyanelle of Cyanophora paradoxa and the mitochondrion of the flagellate Reclinomonas americana[10,17,18]