989 resultados para Information visualization
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An Internet portal accessible at www.gdb.unibe.ch has been set up to automatically generate color-coded similarity maps of the ChEMBL database in relation to up to two sets of active compounds taken from the enhanced Directory of Useful Decoys (eDUD), a random set of molecules, or up to two sets of user-defined reference molecules. These maps visualize the relationships between the selected compounds and ChEMBL in six different high dimensional chemical spaces, namely MQN (42-D molecular quantum numbers), SMIfp (34-D SMILES fingerprint), APfp (20-D shape fingerprint), Xfp (55-D pharmacophore fingerprint), Sfp (1024-bit substructure fingerprint), and ECfp4 (1024-bit extended connectivity fingerprint). The maps are supplied in form of Java based desktop applications called “similarity mapplets” allowing interactive content browsing and linked to a “Multifingerprint Browser for ChEMBL” (also accessible directly at www.gdb.unibe.ch) to perform nearest neighbor searches. One can obtain six similarity mapplets of ChEMBL relative to random reference compounds, 606 similarity mapplets relative to single eDUD active sets, 30 300 similarity mapplets relative to pairs of eDUD active sets, and any number of similarity mapplets relative to user-defined reference sets to help visualize the structural diversity of compound series in drug optimization projects and their relationship to other known bioactive compounds.
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BACKGROUND INFORMATION Over the past decades, cryo-electron microscopy of vitrified specimens has yielded a detailed understanding of the tubulin and microtubule structures of samples reassembled in vitro from purified components. However, our knowledge of microtubule structure in vivo remains limited by the chemical treatments commonly used to observe cellular architecture using electron microscopy. RESULTS We used cryo-electron microscopy and cryo-electron tomography of vitreous sections to investigate the ultrastructure of microtubules in their cellular context. Vitreous sections were obtained from organotypic slices of rat hippocampus and from Chinese-hamster ovary cells in culture. Microtubules revealed their protofilament ultrastructure, polarity and, in the most favourable cases, molecular details comparable with those visualized in three-dimensional reconstructions of microtubules reassembled in vitro from purified tubulin. The resolution of the tomograms was estimated to be approx. 4 nm, which enabled the detection of luminal particles of approx. 6 nm in diameter inside microtubules. CONCLUSIONS The present study provides a first step towards a description of microtubules, in addition to other macromolecular assemblies, in an unperturbed cellular context at the molecular level. As the resolution appears to be similar to that obtainable with plunge-frozen samples, it should allow for the in vivo identification of larger macromolecular assemblies in vitreous sections of whole cells and tissues.
Direct visualization of the outer membrane of mycobacteria and corynebacteria in their native state.
Resumo:
The cell envelope of mycobacteria, which include the causative agents of tuberculosis and leprosy, is crucial for their success as pathogens. Despite a continued strong emphasis on identifying the multiple chemical components of this envelope, it has proven difficult to combine its components into a comprehensive structural model, primarily because the available ultrastructural data rely on conventional electron microscopy embedding and sectioning, which are known to induce artifacts. The existence of an outer membrane bilayer has long been postulated but has never been directly observed by electron microscopy of ultrathin sections. Here we have used cryo-electron microscopy of vitreous sections (CEMOVIS) to perform a detailed ultrastructural analysis of three species belonging to the Corynebacterineae suborder, namely, Mycobacterium bovis BCG, Mycobacterium smegmatis, and Corynebacterium glutamicum, in their native state. We provide new information that accurately describes the different layers of the mycobacterial cell envelope and challenges current models of the organization of its components. We show a direct visualization of an outer membrane, analogous to that found in gram-negative bacteria, in the three bacterial species examined. Furthermore, we demonstrate that mycolic acids, the hallmark of mycobacteria and related genera, are essential for the formation of this outer membrane. In addition, a granular layer and a low-density zone typifying the periplasmic space of gram-positive bacteria are apparent in CEMOVIS images of mycobacteria and corynebacteria. Based on our observations, a model of the organization of the lipids in the outer membrane is proposed. The architecture we describe should serve as a reference for future studies to relate the structure of the mycobacterial cell envelope to its function.
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The reporting of outputs from health surveillance systems should be done in a near real-time and interactive manner in order to provide decision makers with powerful means to identify, assess, and manage health hazards as early and efficiently as possible. While this is currently rarely the case in veterinary public health surveillance, reporting tools do exist for the visual exploration and interactive interrogation of health data. In this work, we used tools freely available from the Google Maps and Charts library to develop a web application reporting health-related data derived from slaughterhouse surveillance and from a newly established web-based equine surveillance system in Switzerland. Both sets of tools allowed entry-level usage without or with minimal programing skills while being flexible enough to cater for more complex scenarios for users with greater programing skills. In particular, interfaces linking statistical softwares and Google tools provide additional analytical functionality (such as algorithms for the detection of unusually high case occurrences) for inclusion in the reporting process. We show that such powerful approaches could improve timely dissemination and communication of technical information to decision makers and other stakeholders and could foster the early-warning capacity of animal health surveillance systems.
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The control part of the execution of a constraint logic program can be conceptually shown as a search-tree, where nodes correspond to calis, and whose branches represent conjunctions and disjunctions. This tree represents the search space traversed by the program, and has also a direct relationship with the amount of work performed by the program. The nodes of the tree can be used to display information regarding the state and origin of instantiation of the variables involved in each cali. This depiction can also be used for the enumeration process. These are the features implemented in APT, a tool which runs constraint logic programs while depicting a (modified) search-tree, keeping at the same time information about the state of the variables at every moment in the execution. This information can be used to replay the execution at will, both forwards and backwards in time. These views can be abstracted when the size of the execution requires it. The search-tree view is used as a framework onto which constraint-level visualizations (such as those presented in the following chapter) can be attached.
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Visualization of program executions has been used in applications which include education and debugging. However, traditional visualization techniques often fall short of expectations or are altogether inadequate for new programming paradigms, such as Constraint Logic Programming (CLP), whose declarative and operational semantics differ in some crucial ways from those of other paradigms. In particular, traditional ideas regarding the behavior of data often cannot be lifted in a straightforward way to (C)LP from other families of programming languages. In this chapter we discuss techniques for visualizing data evolution in CLP. We briefly review some previously proposed visualization paradigms, and also propose a number of (to our knowledge) novel ones. The graphical representations have been chosen based on the perceived needs of a programmer trying to analyze the behavior and characteristics of an execution. In particular, we concéntrate on the representation of the run-time valúes of the variables, and the constraints among them. Given our interest in visualizing large executions, we also pay attention to abstraction techniques, i.e., techniques which are intended to help in reducing the complexity of the visual information.
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Visualization of program executions has been found useful in applications which include education and debugging. However, traditional visualization techniques often fall short of expectations or are altogether inadequate for new programming paradigms, such as Constraint Logic Programming (CLP), whose declarative and operational semantics differ in some crucial ways from those of other paradigms. In particular, traditional ideas regarding flow control and the behavior of data often cannot be lifted in a straightforward way to (C)LP from other families of programming languages. In this paper we discuss techniques for visualizing program execution and data evolution in CLP. We briefly review some previously proposed visualization paradigms, and also propose a number of (to our knowledge) novel ones. The graphical representations have been chosen based on the perceived needs of a programmer trying to analyze the behavior and characteristics of an execution. In particular, we concéntrate on the representation of the program execution behavior (control), the runtime valúes of the variables, and the runtime constraints. Given our interest in visualizing large executions, we also pay attention to abstraction techniques, Le., techniques which are intended to help in reducing the complexity of the visual information.
Resumo:
Virtual reality (VR) techniques to understand and obtain conclusions of data in an easy way are being used by the scientific community. However, these techniques are not used frequently for analyzing large amounts of data in life sciences, particularly in genomics, due to the high complexity of data (curse of dimensionality). Nevertheless, new approaches that allow to bring out the real important data characteristics, arise the possibility of constructing VR spaces to visually understand the intrinsic nature of data. It is well known the benefits of representing high dimensional data in tridimensional spaces by means of dimensionality reduction and transformation techniques, complemented with a strong component of interaction methods. Thus, a novel framework, designed for helping to visualize and interact with data about diseases, is presented. In this paper, the framework is applied to the Van't Veer breast cancer dataset is used, while oncologists from La Paz Hospital (Madrid) are interacting with the obtained results. That is to say a first attempt to generate a visually tangible model of breast cancer disease in order to support the experience of oncologists is presented.
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Acquired brain injury (ABI) 1-2 refers to any brain damage occurring after birth. It usually causes certain damage to portions of the brain. ABI may result in a significant impairment of an individuals physical, cognitive and/or psychosocial functioning. The main causes are traumatic brain injury (TBI), cerebrovascular accident (CVA) and brain tumors. The main consequence of ABI is a dramatic change in the individuals daily life. This change involves a disruption of the family, a loss of future income capacity and an increase of lifetime cost. One of the main challenges in neurorehabilitation is to obtain a dysfunctional profile of each patient in order to personalize the treatment. This paper proposes a system to generate a patient s dysfunctional profile by integrating theoretical, structural and neuropsychological information on a 3D brain imaging-based model. The main goal of this dysfunctional profile is to help therapists design the most suitable treatment for each patient. At the same time, the results obtained are a source of clinical evidence to improve the accuracy and quality of our rehabilitation system. Figure 1 shows the diagram of the system. This system is composed of four main modules: image-based extraction of parameters, theoretical modeling, classification and co-registration and visualization module.
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In this paper we provide a method that allows the visualization of similarity relationships present between items of collaborative filtering recommender systems, as well as the relative importance of each of these. The objective is to offer visual representations of the recommender system?s set of items and of their relationships; these graphs show us where the most representative information can be found and which items are rated in a more similar way by the recommender system?s community of users. The visual representations achieved take the shape of phylogenetic trees, displaying the numerical similarity and the reliability between each pair of items considered to be similar. As a case study we provide the results obtained using the public database Movielens 1M, which contains 3900 movies.
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Geographic information technologies (GIT) are essential to many fields of research, such as the preservation and dissemination of cultural heritage buildings, a category which includes traditional underground wine cellars. This article presents a methodology based on research carried out on this type of rural heritage building. The data were acquired using the following sensors: EDM, total station, close-range photogrammetry and laser scanning, and subsequently processed with a specific software which was verified for each case, in order to obtain a satisfactory graphic representation of these underground wine cellars. Two key aspects of this work are the accuracy of the data processing and the visualization of these traditional constructions. The methodology includes an application for geovisualizing these traditional constructions on mobile devices in order to contribute to raising awareness of this unique heritage.
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Over the last few years, the Data Center market has increased exponentially and this tendency continues today. As a direct consequence of this trend, the industry is pushing the development and implementation of different new technologies that would improve the energy consumption efficiency of data centers. An adaptive dashboard would allow the user to monitor the most important parameters of a data center in real time. For that reason, monitoring companies work with IoT big data filtering tools and cloud computing systems to handle the amounts of data obtained from the sensors placed in a data center.Analyzing the market trends in this field we can affirm that the study of predictive algorithms has become an essential area for competitive IT companies. Complex algorithms are used to forecast risk situations based on historical data and warn the user in case of danger. Considering that several different users will interact with this dashboard from IT experts or maintenance staff to accounting managers, it is vital to personalize it automatically. Following that line of though, the dashboard should only show relevant metrics to the user in different formats like overlapped maps or representative graphs among others. These maps will show all the information needed in a visual and easy-to-evaluate way. To sum up, this dashboard will allow the user to visualize and control a wide range of variables. Monitoring essential factors such as average temperature, gradients or hotspots as well as energy and power consumption and savings by rack or building would allow the client to understand how his equipment is behaving, helping him to optimize the energy consumption and efficiency of the racks. It also would help him to prevent possible damages in the equipment with predictive high-tech algorithms.
Resumo:
his paper discusses a process to graphically view and analyze information obtained from a network of urban streets, using an algorithm that establishes a ranking of importance of the nodes of the network itself. The basis of this process is to quantify the network information obtained by assigning numerical values to each node, representing numerically the information. These values are used to construct a data matrix that allows us to apply a classification algorithm of nodes in a network in order of importance. From this numerical ranking of the nodes, the process finish with the graphical visualization of the network. An example is shown to illustrate the whole process.
Resumo:
BACKGROUND INFORMATION The Plasmodium parasite, during its life cycle, undergoes three phases of asexual reproduction, these being repeated rounds of erythrocytic schizogony, sporogony within oocysts on the mosquito midgut wall and exo-erythrocytic schizogony within the hepatocyte. During each phase of asexual reproduction, the parasite must ensure that every new daughter cell contains an apicoplast, as this organelle cannot be formed de novo and is essential for parasite survival. To date, studies visualizing the apicoplast in live Plasmodium parasites have been restricted to the blood stages of Plasmodium falciparum. RESULTS In the present study, we have generated Plasmodium berghei parasites in which GFP (green fluorescent protein) is targeted to the apicoplast using the specific targeting sequence of ACP (acyl carrier protein), which has allowed us to visualize this organelle in live Plasmodium parasites. During each phase of asexual reproduction, the apicoplast becomes highly branched, but remains as a single organelle until the completion of nuclear division, whereupon it divides and is rapidly segregated into newly forming daughter cells. We have shown that the antimicrobial agents azithromycin, clindamycin and doxycycline block development of the apicoplast during exo-erythrocytic schizogony in vitro, leading to impaired parasite maturation. CONCLUSIONS Using a range of powerful live microscopy techniques, we show for the first time the development of a Plasmodium organelle through the entire life cycle of the parasite. Evidence is provided that interference with the development of the Plasmodium apicoplast results in the failure to produce red-blood-cell-infective merozoites.
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Research analysis of electrocardiograms (ECG) today is carried out mostly using time depending signals of different leads shown in the graphs. Definition of ECG parameters is performed by qualified personnel, and requiring particular skills. To support decoding the cardiac depolarization phase of ECG there are methods to analyze space-time convolution charts in three dimensions where the heartbeat is described by the trajectory of its electrical vector. Based on this, it can be assumed that all available options of the classical ECG analysis of this time segment can be obtained using this technique. Investigated ECG visualization techniques in three dimensions combined with quantitative methods giving additional features of cardiac depolarization and allow a better exploitation of the information content of the given ECG signals.