878 resultados para design-based inference
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Magdeburg, Univ., Fak. für Elektrotechnik und Informationstechnik, Diss., 2012
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ABSTRACT The drug discovery process has been profoundly changed recently by the adoption of computational methods helping the design of new drug candidates more rapidly and at lower costs. In silico drug design consists of a collection of tools helping to make rational decisions at the different steps of the drug discovery process, such as the identification of a biomolecular target of therapeutical interest, the selection or the design of new lead compounds and their modification to obtain better affinities, as well as pharmacokinetic and pharmacodynamic properties. Among the different tools available, a particular emphasis is placed in this review on molecular docking, virtual high throughput screening and fragment-based ligand design.
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Malaria is responsible for more deaths around the world than any other parasitic disease. Due to the emergence of strains that are resistant to the current chemotherapeutic antimalarial arsenal, the search for new antimalarial drugs remains urgent though hampered by a lack of knowledge regarding the molecular mechanisms of artemisinin resistance. Semisynthetic compounds derived from diterpenes from the medicinal plant Wedelia paludosawere tested in silico against the Plasmodium falciparumCa2+-ATPase, PfATP6. This protein was constructed by comparative modelling using the three-dimensional structure of a homologous protein, 1IWO, as a scaffold. Compound 21 showed the best docking scores, indicating a better interaction with PfATP6 than that of thapsigargin, the natural inhibitor. Inhibition of PfATP6 by diterpene compounds could promote a change in calcium homeostasis, leading to parasite death. These data suggest PfATP6 as a potential target for the antimalarial ent-kaurane diterpenes.
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We have previously shown that a 28-amino acid peptide derived from the BRC4 motif of BRCA2 tumor suppressor inhibits selectively human RAD51 recombinase (HsRad51). With the aim of designing better inhibitors for cancer treatment, we combined an in silico docking approach with in vitro biochemical testing to construct a highly efficient chimera peptide from eight existing human BRC motifs. We built a molecular model of all BRC motifs complexed with HsRad51 based on the crystal structure of the BRC4 motif-HsRad51 complex, computed the interaction energy of each residue in each BRC motif, and selected the best amino acid residue at each binding position. This analysis enabled us to propose four amino acid substitutions in the BRC4 motif. Three of these increased the inhibitory effect in vitro, and this effect was found to be additive. We thus obtained a peptide that is about 10 times more efficient in inhibiting HsRad51-ssDNA complex formation than the original peptide.
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This paper introduces Collage, a high-level IMS-LD compliant authoring tool that is specialized for CSCL (Computer-Supported Collaborative Learning). Nowadays CSCL is a key trend in elearning since it highlights the importance of social interactions as an essential element of learning. CSCL is an interdisciplinary domain, which demands participatory design techniques that allow teachers to get directly involved in design activities. Developing CSCL designs using LD is a difficult task for teachers since LD is a complex technical specification and modelling collaborative characteristics can be tricky. Collage helps teachers in the process of creating their own potentially effective collaborative Learning Designs by reusing and customizing patterns, according to the requirements of a particular learning situation. These patterns, called Collaborative Learning Flow Patterns (CLFPs), represent best practices that are repetitively used by practitioners when structuring the flow of (collaborative) learning activities. An example of an LD that can be created using Collage is illustrated in the paper. Preliminary evaluation results show that teachers, with experience in CL but without LD knowledge, can successfully design real collaborative learning experiences using Collage.
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Collage is a pattern-based visual design authoring tool for the creation of collaborative learning scripts computationally modelled with IMS Learning Design (LD). The pattern-based visual approach aims to provide teachers with design ideas that are based on broadly accepted practices. Besides, it seeks hiding the LD notation so that teachers can easily create their own designs. The use of visual representations supports both the understanding of the design ideas and the usability of the authoring tool. This paper presents a multicase study comprising three different cases that evaluate the approach from different perspectives. The first case includes workshops where teachers use Collage. A second case implies the design of a scenario proposed by a third-party using related approaches. The third case analyzes a situation where students follow a design created with Collage. The cross-case analysis provides a global understanding of the possibilities and limitations of the pattern-based visual design approach.
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Aim Recently developed parametric methods in historical biogeography allow researchers to integrate temporal and palaeogeographical information into the reconstruction of biogeographical scenarios, thus overcoming a known bias of parsimony-based approaches. Here, we compare a parametric method, dispersal-extinction-cladogenesis (DEC), against a parsimony-based method, dispersal-vicariance analysis (DIVA), which does not incorporate branch lengths but accounts for phylogenetic uncertainty through a Bayesian empirical approach (Bayes-DIVA). We analyse the benefits and limitations of each method using the cosmopolitan plant family Sapindaceae as a case study.Location World-wide.Methods Phylogenetic relationships were estimated by Bayesian inference on a large dataset representing generic diversity within Sapindaceae. Lineage divergence times were estimated by penalized likelihood over a sample of trees from the posterior distribution of the phylogeny to account for dating uncertainty in biogeographical reconstructions. We compared biogeographical scenarios between Bayes-DIVA and two different DEC models: one with no geological constraints and another that employed a stratified palaeogeographical model in which dispersal rates were scaled according to area connectivity across four time slices, reflecting the changing continental configuration over the last 110 million years.Results Despite differences in the underlying biogeographical model, Bayes-DIVA and DEC inferred similar biogeographical scenarios. The main differences were: (1) in the timing of dispersal events - which in Bayes-DIVA sometimes conflicts with palaeogeographical information, and (2) in the lower frequency of terminal dispersal events inferred by DEC. Uncertainty in divergence time estimations influenced both the inference of ancestral ranges and the decisiveness with which an area can be assigned to a node.Main conclusions By considering lineage divergence times, the DEC method gives more accurate reconstructions that are in agreement with palaeogeographical evidence. In contrast, Bayes-DIVA showed the highest decisiveness in unequivocally reconstructing ancestral ranges, probably reflecting its ability to integrate phylogenetic uncertainty. Care should be taken in defining the palaeogeographical model in DEC because of the possibility of overestimating the frequency of extinction events, or of inferring ancestral ranges that are outside the extant species ranges, owing to dispersal constraints enforced by the model. The wide-spanning spatial and temporal model proposed here could prove useful for testing large-scale biogeographical patterns in plants.
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The HbpR protein is the sigma54-dependent transcription activator for 2-hydroxybiphenyl degradation in Pseudomonas azelaica. The ability of HbpR and XylR, which share 35% amino acid sequence identity, to cross-activate the PhbpC and Pu promoters was investigated by determining HbpR- or XylR-mediated luciferase expression and by DNA binding assays. XylR measurably activated the PhbpC promoter in the presence of the effector m-xylene, both in Escherichia coli and Pseudomonas putida. HbpR weakly stimulated the Pu promoter in E. coli but not in P. azelaica. Poor HbpR-dependent activation from Pu was caused by a weak binding to the operator region. To create promoters efficiently activated by both regulators, the HbpR binding sites on PhbpC were gradually changed into the XylR binding sites of Pu by site-directed mutagenesis. Inducible luciferase expression from mutated promoters was tested in E. coli on a two plasmid system, and from mono copy gene fusions in P. azelaica and P. putida. Some mutants were efficiently activated by both HbpR and XylR, showing that promoters can be created which are permissive for both regulators. Others achieved a higher XylR-dependent transcription than from Pu itself. Mutants were also obtained which displayed a tenfold lower uninduced expression level by HbpR than the wild-type PhbpC, while keeping the same maximal induction level. On the basis of these results, a dual-responsive bioreporter strain of P. azelaica was created, containing both XylR and HbpR, and activating luciferase expression from the same single promoter independently with m-xylene and 2-hydroxybiphenyl.
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Animal dispersal in a fragmented landscape depends on the complex interaction between landscape structure and animal behavior. To better understand how individuals disperse, it is important to explicitly represent the properties of organisms and the landscape in which they move. A common approach to modelling dispersal includes representing the landscape as a grid of equal sized cells and then simulating individual movement as a correlated random walk. This approach uses a priori scale of resolution, which limits the representation of all landscape features and how different dispersal abilities are modelled. We develop a vector-based landscape model coupled with an object-oriented model for animal dispersal. In this spatially explicit dispersal model, landscape features are defined based on their geographic and thematic properties and dispersal is modelled through consideration of an organism's behavior, movement rules and searching strategies (such as visual cues). We present the model's underlying concepts, its ability to adequately represent landscape features and provide simulation of dispersal according to different dispersal abilities. We demonstrate the potential of the model by simulating two virtual species in a real Swiss landscape. This illustrates the model's ability to simulate complex dispersal processes and provides information about dispersal such as colonization probability and spatial distribution of the organism's path
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Context: Until now, the testosterone/epitestosterone (T/E) ratio is the main marker for detection of testosterone (T) misuse in athletes. As this marker can be influenced by a number of confounding factors, additional steroid profile parameters indicating T misuse can provide substantiating evidence of doping with endogenous steroids. The evaluation of a steroid profile is currently based upon population statistics. Since large inter-individual variations exist, a paradigm shift towards subject-based references is ongoing in doping analysis. Objective: Proposition of new biomarkers for the detection of testosterone in sports using extensive steroid profiling and an adaptive model based upon Bayesian inference. Subjects: 6 healthy male volunteers were administered with testosterone undecanoate. Population statistics were performed upon steroid profiles from 2014 male Caucasian athletes participating in official sport competition. Design: An extended search for new biomarkers in a comprehensive steroid profile combined with Bayesian inference techniques as used in the Athlete Biological Passport resulted in a selection of additional biomarkers that may improve detection of testosterone misuse in sports. Results: Apart from T/E, 4 other steroid ratios (6α-OH-androstenedione/16α-OH-dehydroepiandrostenedione, 4-OH-androstenedione/16α-OH-androstenedione, 7α-OH-testosterone/7β-OH-dehydroepiandrostenedione and dihydrotestosterone/5β-androstane-3α,17β-diol) were identified as sensitive urinary biomarkers for T misuse. These new biomarkers were rated according to relative response, parameter stability, detection time and discriminative power. Conclusion: Newly selected biomarkers were found suitable for individual referencing within the concept of the Athlete's Biological Passport. The parameters showed improved detection time and discriminative power compared to the T/E ratio. Such biomarkers can support the evidence of doping with small oral doses of testosterone.
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This article presents preliminary research from an instructional design perspective on the design of the case method as an integral part of pedagogy and technology. Key features and benefitsusing this teaching and learning strategy in a Virtual Teaching and Learning Environment(VTLE) are identified, taking into account the requirements of the European Higher Education Area (EHEA) for a competence-based curricula design. The implications of these findings for alearning object approach exploring the possibilities of learning personalization, reusability and interoperability trough IMS LD, are also analyzed.
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The integrated system of design for manufacturing and assembly (DFMA) and internet based collaborative design are presented to support product design, manufacturing process, and assembly planning for axial eccentric oil-pump design. The presented system manages and schedules group oriented collaborative activities. The design guidelines of internet based collaborative design & DFMA are expressed. The components and the manufacturing stages of axial eccentric oil-pump are expressed in detail. The file formats of the presented system include the data types of collaborative design of the product, assembly design, assembly planning and assembly system design. Product design and assembly planning can be operated synchronously and intelligently and they are integrated under the condition of internet based collaborative design and DFMA. The technologies of collaborative modelling, collaborative manufacturing, and internet based collaborative assembly for the specific pump construction are developed. A seven-security level is presented to ensure the security of the internet based collaborative design system.
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This paper analyzes the possibilities of integrating cost information and engineering design. Special emphasis is on finding the potential of using the activity-based costing (ABC) method when formulating cost information for the needs of design engineers. This paper suggests that ABC is more useful than the traditional job order costing, but the negative issue is the fact that ABC models become easily too complicated, i.e. expensive to build and maintain, and difficult to use. For engineering design the most suitable elements of ABC are recognizing activities of the company, constructing acitivity chains, identifying resources, activity and cost drivers, as wellas calculating accurate product costs. ABC systems including numerous cost drivers can become complex. Therefore, a comprehensive ABC based cost information system for the use of design engineers should be considered criticaly. Combining the suitable ideas of ABC with engineering oriented thinking could give competentresults.