A novel XML document structure comparison framework based-on sub-tree commonalities and label semantics

XML similarity evaluation has become a central issue in the database and information communities, its applications ranging over document clustering, version control, data integration and ranked retrieval. Various algorithms for comparing hierarchically structured data, XML documents in particular, have been proposed in the literature. Most of them make use of techniques for finding the edit distance between tree structures, XML documents being commonly modeled as Ordered Labeled Trees. Yet, a thorough investigation of current approaches led us to identify several similarity aspects, i.e., sub-tree related structural and semantic similarities, which are not sufficiently addressed while comparing XML documents. In this paper, we provide an integrated and fine-grained comparison framework to deal with both structural and semantic similarities in XML documents (detecting the occurrences and repetitions of structurally and semantically similar sub-trees), and to allow the end-user to adjust the comparison process according to her requirements. Our framework consists of four main modules for (i) discovering the structural commonalities between sub-trees, (ii) identifying sub-tree semantic resemblances, (iii) computing tree-based edit operations costs, and (iv) computing tree edit distance. Experimental results demonstrate higher comparison accuracy with respect to alternative methods, while timing experiments reflect the impact of semantic similarity on overall system performance.

A tellurium-based cathepsin B inhibitor: Molecular structure, modelling, molecular docking and biological evaluation

The crystallographically determined structure of biologically active 4,4-dichloro-1,3-diphenyl-4-telluraoct-2-en-1-one, 3, shows the coordination geometry for Te to be distorted psi-pentagonal bipyramidal based on a C2OCl3(lone pair) donor set. Notable is the presence of an intramolecular axial Te center dot center dot center dot O (carbonyl) interaction, a design element included to reduce hydrolysis. Raman and molecular modelling studies indicate the persistence of the Te center dot center dot center dot O(carbonyl) interaction in the solution (CHCl3) and gasphases, respectively. Docking studies of 3' (i.e. original 3 less one chloride) with Cathepsin B reveals a change in the configuration about the vinyl C = C bond. i.e. to E from Z (crystal structure). This isomerism allows the optimisation of interactions in the complex which features a covalent Te-SGCys29 bond. Crucially, the E configuration observed for 3' allows for the formation of a hypervalent Te center dot center dot center dot O interaction as well as an O center dot center dot center dot H-O hydrogen bond with the Gly27 and Glu122 residues, respectively. Additional stabilisation is afforded by a combination of interactions spanning the S1, S2, S1' and S2' sub-sites of Cathepsin B. The greater experimental inhibitory activity of 3 compared with analogues is rationalised by the additional interactions formed between 3' and the His110 and His111 residues in the occluding loop, which serve to hinder the entrance to the active site. (C) 2012 Elsevier B.V. All rights reserved.

Computational methods for the analysis of protein structure and function

The vast majority of known proteins have not yet been experimentally characterized and little is known about their function. The design and implementation of computational tools can provide insight into the function of proteins based on their sequence, their structure, their evolutionary history and their association with other proteins. Knowledge of the three-dimensional (3D) structure of a protein can lead to a deep understanding of its mode of action and interaction, but currently the structures of <1% of sequences have been experimentally solved. For this reason, it became urgent to develop new methods that are able to computationally extract relevant information from protein sequence and structure. The starting point of my work has been the study of the properties of contacts between protein residues, since they constrain protein folding and characterize different protein structures. Prediction of residue contacts in proteins is an interesting problem whose solution may be useful in protein folding recognition and de novo design. The prediction of these contacts requires the study of the protein inter-residue distances related to the specific type of amino acid pair that are encoded in the so-called contact map. An interesting new way of analyzing those structures came out when network studies were introduced, with pivotal papers demonstrating that protein contact networks also exhibit small-world behavior. In order to highlight constraints for the prediction of protein contact maps and for applications in the field of protein structure prediction and/or reconstruction from experimentally determined contact maps, I studied to which extent the characteristic path length and clustering coefficient of the protein contacts network are values that reveal characteristic features of protein contact maps. Provided that residue contacts are known for a protein sequence, the major features of its 3D structure could be deduced by combining this knowledge with correctly predicted motifs of secondary structure. In the second part of my work I focused on a particular protein structural motif, the coiled-coil, known to mediate a variety of fundamental biological interactions. Coiled-coils are found in a variety of structural forms and in a wide range of proteins including, for example, small units such as leucine zippers that drive the dimerization of many transcription factors or more complex structures such as the family of viral proteins responsible for virus-host membrane fusion. The coiled-coil structural motif is estimated to account for 5-10% of the protein sequences in the various genomes. Given their biological importance, in my work I introduced a Hidden Markov Model (HMM) that exploits the evolutionary information derived from multiple sequence alignments, to predict coiled-coil regions and to discriminate coiled-coil sequences. The results indicate that the new HMM outperforms all the existing programs and can be adopted for the coiled-coil prediction and for large-scale genome annotation. Genome annotation is a key issue in modern computational biology, being the starting point towards the understanding of the complex processes involved in biological networks. The rapid growth in the number of protein sequences and structures available poses new fundamental problems that still deserve an interpretation. Nevertheless, these data are at the basis of the design of new strategies for tackling problems such as the prediction of protein structure and function. Experimental determination of the functions of all these proteins would be a hugely time-consuming and costly task and, in most instances, has not been carried out. As an example, currently, approximately only 20% of annotated proteins in the Homo sapiens genome have been experimentally characterized. A commonly adopted procedure for annotating protein sequences relies on the "inheritance through homology" based on the notion that similar sequences share similar functions and structures. This procedure consists in the assignment of sequences to a specific group of functionally related sequences which had been grouped through clustering techniques. The clustering procedure is based on suitable similarity rules, since predicting protein structure and function from sequence largely depends on the value of sequence identity. However, additional levels of complexity are due to multi-domain proteins, to proteins that share common domains but that do not necessarily share the same function, to the finding that different combinations of shared domains can lead to different biological roles. In the last part of this study I developed and validate a system that contributes to sequence annotation by taking advantage of a validated transfer through inheritance procedure of the molecular functions and of the structural templates. After a cross-genome comparison with the BLAST program, clusters were built on the basis of two stringent constraints on sequence identity and coverage of the alignment. The adopted measure explicity answers to the problem of multi-domain proteins annotation and allows a fine grain division of the whole set of proteomes used, that ensures cluster homogeneity in terms of sequence length. A high level of coverage of structure templates on the length of protein sequences within clusters ensures that multi-domain proteins when present can be templates for sequences of similar length. This annotation procedure includes the possibility of reliably transferring statistically validated functions and structures to sequences considering information available in the present data bases of molecular functions and structures.

Tailoring, synthesis and structure-property relationships of 2,3-thienoimide based molecular materials

Organic molecular semiconductors are subject of intense research for their crucial role as key components of new generation low cost, flexible, and large area electronic devices such as displays, thin-film transistors, solar cells, sensors and logic circuits. In particular, small molecular thienoimide (TI) based materials are emerging as novel multifunctional materials combining a good processability together to ambipolar or n-type charge transport and electroluminescence at the solid state, thus enabling the fabrication of integrated devices like organic field effect transistors (OFETs) and light emitting transistor (OLETs). Given this peculiar combination of characteristics, they also constitute the ideal substrates for fundamental studies on the structure-property relationships in multifunctional molecular systems. In this scenario, this thesis work is focused on the synthesis of new thienoimide based materials with tunable optical, packing, morphology, charge transport and electroluminescence properties by following a fine molecular tailoring, thus optimizing their performances in device as well as investigating and enabling new applications. Investigation on their structure-property relationships has been carried out and in particular, the effect of different π-conjugated cores (heterocycles, length) and alkyl end chain (shape, length) changes have been studied, obtaining materials with enhanced electron transport capability end electroluminescence suitable for the realization of OFETs and single layer OLETs. Moreover, control on the polymorphic behaviour characterizing thienoimide materials has been reached by synthetic and post-synthetic methodologies, developing multifunctional materials from a single polymorphic compound. Finally, with the aim of synthesizing highly pure materials, simplifying the purification steps and avoiding organometallic residues, procedures based on direct arylation reactions replacing conventional cross-couplings have been investigated and applied to different classes of molecules, bearing thienoimidic core or ends, as well as thiophene and anthracene derivatives, validating this approach as a clean alternative for the synthesis of several molecular materials.

Application of an in vitro drug screening assay based on the release of phosphoglucose isomerase to determine the structure-activity relationship of thiazolides against Echinococcus multilocularis metacestodes

OBJECTIVES: The disease alveolar echinococcosis (AE), caused by the larval stage of the cestode Echinococcus multilocularis, is fatal if treatment is unsuccessful. Current treatment options are, at best, parasitostatic, and involve taking benzimidazoles (albendazole, mebendazole) for the whole of a patient's life. In conjunction with the recent development of optimized procedures for E. multilocularis metacestode cultivation, we aimed to develop a rapid and reliable drug screening test, which enables efficient screening of a large number of compounds in a relatively short time frame. METHODS: Metacestodes were treated in vitro with albendazole, the nitro-thiazole nitazoxanide and 29 nitazoxanide derivatives. The resulting leakage of phosphoglucose isomerase (PGI) activity into the medium supernatant was measured and provided an indication of compound efficacy. RESULTS: We show that upon in vitro culture of E. multilocularis metacestodes in the presence of active drugs such as albendazole, the nitro-thiazole nitazoxanide and 30 different nitazoxanide derivatives, the activity of PGI in culture supernatants increased. The increase in PGI activity correlated with the progressive degeneration and destruction of metacestode tissue in a time- and concentration-dependent manner, which allowed us to perform a structure-activity relationship analysis on the thiazolide compounds used in this study. CONCLUSIONS: The assay presented here is inexpensive, rapid, can be used in 24- and 96-well formats and will serve as an ideal tool for first-round in vitro tests on the efficacy of large numbers of antiparasitic compounds.

Landscape and forest structure at moose mortality sites on Isle Royale National Park. A LiDAR based assessment

Landscape structure and heterogeneity play a potentially important, but little understood role in predator-prey interactions and behaviourally-mediated habitat selection. For example, habitat complexity may either reduce or enhance the efficiency of a predator's efforts to search, track, capture, kill and consume prey. For prey, structural heterogeneity may affect predator detection, avoidance and defense, escape tactics, and the ability to exploit refuges. This study, investigates whether and how vegetation and topographic structure influence the spatial patterns and distribution of moose (Alces alces) mortality due to predation and malnutrition at the local and landscape levels on Isle Royale National Park. 230 locations where wolves (Canis lupus) killed moose during the winters between 2002 and 2010, and 182 moose starvation death sites for the period 1996-2010, were selected from the extensive Isle Royale Wolf-Moose Project carcass database. A variety of LiDAR-derived metrics were generated and used in an algorithm model (Random Forest) to identify, characterize, and classify three-dimensional variables significant to each of the mortality classes. Furthermore, spatial models to predict and assess the likelihood at the landscape scale of moose mortality were developed. This research found that the patterns of moose mortality by predation and malnutrition across the landscape are non-random, have a high degree of spatial variability, and that both mechanisms operate in contexts of comparable physiographic and vegetation structure. Wolf winter hunting locations on Isle Royale are more likely to be a result of its prey habitat selection, although they seem to prioritize the overall areas with higher moose density in the winter. Furthermore, the findings suggest that the distribution of moose mortality by predation is habitat-specific to moose, and not to wolves. In addition, moose sex, age, and health condition also affect mortality site selection, as revealed by subtle differences between sites in vegetation heights, vegetation density, and topography. Vegetation density in particular appears to differentiate mortality locations for distinct classes of moose. The results also emphasize the significance of fine-scale landscape and habitat features when addressing predator-prey interactions. These finer scale findings would be easily missed if analyses were limited to the broader landscape scale alone.

Improved methods for measuring forest landscape structure: LiDAR complements field-based habitat assessment

Conservation and monitoring of forest biodiversity requires reliable information about forest structure and composition at multiple spatial scales. However, detailed data about forest habitat characteristics across large areas are often incomplete due to difficulties associated with field sampling methods. To overcome this limitation we employed a nationally available light detection and ranging (LiDAR) remote sensing dataset to develop variables describing forest landscape structure across a large environmental gradient in Switzerland. Using a model species indicative of structurally rich mountain forests (hazel grouse Bonasa bonasia), we tested the potential of such variables to predict species occurrence and evaluated the additional benefit of LiDAR data when used in combination with traditional, sample plot-based field variables. We calibrated boosted regression trees (BRT) models for both variable sets separately and in combination, and compared the models’ accuracies. While both field-based and LiDAR models performed well, combining the two data sources improved the accuracy of the species’ habitat model. The variables retained from the two datasets held different types of information: field variables mostly quantified food resources and cover in the field and shrub layer, LiDAR variables characterized heterogeneity of vegetation structure which correlated with field variables describing the understory and ground vegetation. When combined with data on forest vegetation composition from field surveys, LiDAR provides valuable complementary information for encompassing species niches more comprehensively. Thus, LiDAR bridges the gap between precise, locally restricted field-data and coarse digital land cover information by reliably identifying habitat structure and quality across large areas.

Age, Growth and Population Structure of Jumbo Flying Squid, Dosidicus Gigas, Based on Statolith Microstructure Off the Exclusive Economic Zone of Chilean Waters

The jumbo flying squid, Dosidicus gigas, support an important squid fishery off the Exclusive Economic Zone of Chilean waters. However, we only have limited information about their biology. In this study, age, growth and population structure of D. gigas were studied using statoliths from 333 specimens (386 females and 147 males) randomly sampled in the Chinese squid jigging surveys from 2007 to 2008 off the Exclusive Economic Zone of Chile. Mantle lengths (MLs) of the sample ranged from 206 to 702 mm, and their ages were estimated from 150 to 307 days for females and from 127 to 302 days for males. At least two spawning groups were identified, the main spawning peak tended to occur between August and November (austral spring group), and the secondary peak appeared during March to June (austral autumn group). The ML-age relationship was best modelled by a linear function for the austral spring group and a power function for the austral autumn group, and the body weight (BW)-age relationship was best described by an exponential function for both the groups. Instantaneous relative growth rates and absolute growth rates for ML and BW did not differ significantly between the two groups. The growth rate of D. gigas tended to be high at young stages, and then decreased after the sub-adult stage (>180 days old). This study suggests large spatial and temporal variability in key life history parameters of D. gigas, calling for the collection of more data with fine spatial and temporal scales to further improve our understanding of the fishery biology of D. gigas.