871 resultados para Geographic information systems -- Data processing
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Background: Expression microarrays are increasingly used to obtain large scale transcriptomic information on a wide range of biological samples. Nevertheless, there is still much debate on the best ways to process data, to design experiments and analyse the output. Furthermore, many of the more sophisticated mathematical approaches to data analysis in the literature remain inaccessible to much of the biological research community. In this study we examine ways of extracting and analysing a large data set obtained using the Agilent long oligonucleotide transcriptomics platform, applied to a set of human macrophage and dendritic cell samples. Results: We describe and validate a series of data extraction, transformation and normalisation steps which are implemented via a new R function. Analysis of replicate normalised reference data demonstrate that intrarray variability is small (only around 2 of the mean log signal), while interarray variability from replicate array measurements has a standard deviation (SD) of around 0.5 log(2) units (6 of mean). The common practise of working with ratios of Cy5/Cy3 signal offers little further improvement in terms of reducing error. Comparison to expression data obtained using Arabidopsis samples demonstrates that the large number of genes in each sample showing a low level of transcription reflect the real complexity of the cellular transcriptome. Multidimensional scaling is used to show that the processed data identifies an underlying structure which reflect some of the key biological variables which define the data set. This structure is robust, allowing reliable comparison of samples collected over a number of years and collected by a variety of operators. Conclusions: This study outlines a robust and easily implemented pipeline for extracting, transforming normalising and visualising transcriptomic array data from Agilent expression platform. The analysis is used to obtain quantitative estimates of the SD arising from experimental (non biological) intra- and interarray variability, and for a lower threshold for determining whether an individual gene is expressed. The study provides a reliable basis for further more extensive studies of the systems biology of eukaryotic cells.
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Smart healthcare is a complex domain for systems integration due to human and technical factors and heterogeneous data sources involved. As a part of smart city, it is such a complex area where clinical functions require smartness of multi-systems collaborations for effective communications among departments, and radiology is one of the areas highly relies on intelligent information integration and communication. Therefore, it faces many challenges regarding integration and its interoperability such as information collision, heterogeneous data sources, policy obstacles, and procedure mismanagement. The purpose of this study is to conduct an analysis of data, semantic, and pragmatic interoperability of systems integration in radiology department, and to develop a pragmatic interoperability framework for guiding the integration. We select an on-going project at a local hospital for undertaking our case study. The project is to achieve data sharing and interoperability among Radiology Information Systems (RIS), Electronic Patient Record (EPR), and Picture Archiving and Communication Systems (PACS). Qualitative data collection and analysis methods are used. The data sources consisted of documentation including publications and internal working papers, one year of non-participant observations and 37 interviews with radiologists, clinicians, directors of IT services, referring clinicians, radiographers, receptionists and secretary. We identified four primary phases of data analysis process for the case study: requirements and barriers identification, integration approach, interoperability measurements, and knowledge foundations. Each phase is discussed and supported by qualitative data. Through the analysis we also develop a pragmatic interoperability framework that summaries the empirical findings and proposes recommendations for guiding the integration in the radiology context.
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Driven by Web 2.0 technology and the almost ubiquitous presence of mobile devices, Volunteered Geographic Information (VGI) is knowing an unprecedented growth. These notable technological advancements have opened fruitful perspectives also in the field of water management and protection, raising the demand for a reconsideration of policies which also takes into account the emerging trend of VGI. This research investigates the opportunity of leveraging such technology to involve citizens equipped with common mobile devices (e.g. tablets and smartphones) in a campaign of report of water-related phenomena. The work is carried out in collaboration with ADBPO - Autorità di bacino del fiume Po (Po river basin Authority), i.e. the entity responsible for the environmental planning and protection of the basin of river Po. This is the longest Italian river, spreading over eight among the twenty Italian Regions and characterized by complex environmental issues. To enrich ADBPO official database with user-generated contents, a FOSS (Free and Open Source Software) architecture was designed which allows not only user field-data collection, but also data Web publication through standard protocols. Open Data Kit suite allows users to collect georeferenced multimedia information using mobile devices equipped with location sensors (e.g. the GPS). Users can report a number of environmental emergencies, problems or simple points of interest related to the Po river basin, taking pictures of them and providing other contextual information. Field-registered data is sent to a server and stored into a PostgreSQL database with PostGIS spatial extension. GeoServer provides then data dissemination on the Web, while specific OpenLayers-based viewers were built to optimize data access on both desktop computers and mobile devices. Besides proving the suitability of FOSS in the frame of VGI, the system represents a successful prototype for the exploitation of user local, real-time information aimed at managing and protecting water resources.
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The computational program called GIS_EM (Geographic Information System for Environmental Monitoring), a software devised to manage geographic information for monitoring soil, surface, and ground water, developed for use in the Health, Safety, and Environment Division of Paulinia Refinery is presented. This program enables registering and management of alphanumeric information pertaining to specific themes such as drilling performed for sample collection and for installation of monitoring wells, geophysical and other tests, results of chemical analyses of soil, surface, and groundwater, as well as reference values providing orientation for soil and water quality, such as EPA, Dutch List, etc. Management of such themes is performed by means of alphanumeric search tools, with specific filters and, in the case of spatial search, through the selection of spatial elements (themes) in map view. Documents existing in digital form, such as reports, photos, maps, may be registered and managed in the network environment. As the system centralizes information generated upon environmental investigations, it expedites access to and search of documents produced and stored in the network environment, minimizing search time and the need to file printed documents. This is an abstract of a paper presented at the AIChE Annual Meeting and Fall Showcase (Cincinnati, OH 10/30/2005-11/4/2005).
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This paper presents an Advanced Traveler Information System (ATIS) developed on Android platform, which is open source and free. The developed application has as its main objective the free use of a Vehicle-to- Infrastructure (V2I) communication through the wireless network access points available in urban centers. In addition to providing the necessary information for an Intelligent Transportation System (ITS) to a central server, the application also receives the traffic data close to the vehicle. Once obtained this traffic information, the application displays them to the driver in a clear and efficient way, allowing the user to make decisions about his route in real time. The application was tested in a real environment and the results are presented in the article. In conclusion we present the benefits of this application. © 2012 IEEE.
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Abstract Background Recent medical and biological technology advances have stimulated the development of new testing systems that have been providing huge, varied amounts of molecular and clinical data. Growing data volumes pose significant challenges for information processing systems in research centers. Additionally, the routines of genomics laboratory are typically characterized by high parallelism in testing and constant procedure changes. Results This paper describes a formal approach to address this challenge through the implementation of a genetic testing management system applied to human genome laboratory. We introduced the Human Genome Research Center Information System (CEGH) in Brazil, a system that is able to support constant changes in human genome testing and can provide patients updated results based on the most recent and validated genetic knowledge. Our approach uses a common repository for process planning to ensure reusability, specification, instantiation, monitoring, and execution of processes, which are defined using a relational database and rigorous control flow specifications based on process algebra (ACP). The main difference between our approach and related works is that we were able to join two important aspects: 1) process scalability achieved through relational database implementation, and 2) correctness of processes using process algebra. Furthermore, the software allows end users to define genetic testing without requiring any knowledge about business process notation or process algebra. Conclusions This paper presents the CEGH information system that is a Laboratory Information Management System (LIMS) based on a formal framework to support genetic testing management for Mendelian disorder studies. We have proved the feasibility and showed usability benefits of a rigorous approach that is able to specify, validate, and perform genetic testing using easy end user interfaces.
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To reach the goals established by the Institute of Medicine (IOM) and the Centers for Disease Control's (CDC) STOP TB USA, measures must be taken to curtail a future peak in Tuberculosis (TB) incidence and speed the currently stagnant rate of TB elimination. Both efforts will require, at minimum, the consideration and understanding of the third dimension of TB transmission: the location-based spread of an airborne pathogen among persons known and unknown to each other. This consideration will require an elucidation of the areas within the U.S. that have endemic TB. The Houston Tuberculosis Initiative (HTI) was a population-based active surveillance of confirmed Houston/Harris County TB cases from 1995–2004. Strengths in this dataset include the molecular characterization of laboratory confirmed cases, the collection of geographic locations (including home addresses) frequented by cases, and the HTI time period that parallels a decline in TB incidence in the United States (U.S.). The HTI dataset was used in this secondary data analysis to implement a GIS analysis of TB cases, the locations frequented by cases, and their association with risk factors associated with TB transmission. ^ This study reports, for the first time, the incidence of TB among the homeless in Houston, Texas. The homeless are an at-risk population for TB disease, yet they are also a population whose TB incidence has been unknown and unreported due to their non-enumeration. The first section of this dissertation identifies local areas in Houston with endemic TB disease. Many Houston TB cases who reported living in these endemic areas also share the TB risk factor of current or recent homelessness. Merging the 2004–2005 Houston enumeration of the homeless with historical HTI surveillance data of TB cases in Houston enabled this first-time report of TB risk among the homeless in Houston. The homeless were more likely to be US-born, belong to a genotypic cluster, and belong to a cluster of a larger size. The calculated average incidence among homeless persons was 411/100,000, compared to 9.5/100,000 among housed. These alarming rates are not driven by a co-infection but by social determinants. The unsheltered persons were hospitalized more days and required more follow-up time by staff than those who reported a steady housing situation. The homeless are a specific example of the increased targeting of prevention dollars that could occur if TB rates were reported for specific areas with known health disparities rather than as a generalized rate normalized over a diverse population. ^ It has been estimated that 27% of Houstonians use public transportation. The city layout allows bus routes to run like veins connecting even the most diverse of populations within the metropolitan area. Secondary data analysis of frequent bus use (defined as riding a route weekly) among TB cases was assessed for its relationship with known TB risk factors. The spatial distribution of genotypic clusters associated with bus use was assessed, along with the reported routes and epidemiologic-links among cases belonging to the identified clusters. ^ TB cases who reported frequent bus use were more likely to have demographic and social risk factors associated with poverty, immune suppression and health disparities. An equal proportion of bus riders and non-bus riders were cultured for Mycobacterium tuberculosis, yet 75% of bus riders were genotypically clustered, indicating recent transmission, compared to 56% of non-bus riders (OR=2.4, 95%CI(2.0, 2.8), p<0.001). Bus riders had a mean cluster size of 50.14 vs. 28.9 (p<0.001). Second order spatial analysis of clustered fingerprint 2 (n=122), a Beijing family cluster, revealed geographic clustering among cases based on their report of bus use. Univariate and multivariate analysis of routes reported by cases belonging to these clusters found that 10 of the 14 clusters were associated with use. Individual Metro routes, including one route servicing the local hospitals, were found to be risk factors for belonging to a cluster shown to be endemic in Houston. The routes themselves geographically connect the census tracts previously identified as having endemic TB. 78% (15/23) of Houston Metro routes investigated had one or more print groups reporting frequent use for every HTI study year. We present data on three specific but clonally related print groups and show that bus-use is clustered in time by route and is the only known link between cases in one of the three prints: print 22. (Abstract shortened by UMI.)^
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In a series of attempts to research and document relevant sloshing type phenomena, a series of experiments have been conducted. The aim of this paper is to describe the setup and data processing of such experiments. A sloshing tank is subjected to angular motion. As a result pressure registers are obtained at several locations, together with the motion data, torque and a collection of image and video information. The experimental rig and the data acquisition systems are described. Useful information for experimental sloshing research practitioners is provided. This information is related to the liquids used in the experiments, the dying techniques, tank building processes, synchronization of acquisition systems, etc. A new procedure for reconstructing experimental data, that takes into account experimental uncertainties, is presented. This procedure is based on a least squares spline approximation of the data. Based on a deterministic approach to the first sloshing wave impact event in a sloshing experiment, an uncertainty analysis procedure of the associated first pressure peak value is described.
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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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The amount of genomic and proteomic data that is entered each day into databases and the experimental literature is outstripping the ability of experimental scientists to keep pace. While generic databases derived from automated curation efforts are useful, most biological scientists tend to focus on a class or family of molecules and their biological impact. Consequently, there is a need for molecular class-specific or other specialized databases. Such databases collect and organize data around a single topic or class of molecules. If curated well, such systems are extremely useful as they allow experimental scientists to obtain a large portion of the available data most relevant to their needs from a single source. We are involved in the development of two such databases with substantial pharmacological relevance. These are the GPCRDB and NucleaRDB information systems, which collect and disseminate data related to G protein-coupled receptors and intra-nuclear hormone receptors, respectively. The GPCRDB was a pilot project aimed at building a generic molecular class-specific database capable of dealing with highly heterogeneous data. A first version of the GPCRDB project has been completed and it is routinely used by thousands of scientists. The NucleaRDB was started recently as an application of the concept for the generalization of this technology. The GPCRDB is available via the WWW at http://www.gpcr.org/7tm/ and the NucleaRDB at http://www.receptors.org/NR/.
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In this paper we describe Fénix, a data model for exchanging information between Natural Language Processing applications. The format proposed is intended to be flexible enough to cover both current and future data structures employed in the field of Computational Linguistics. The Fénix architecture is divided into four separate layers: conceptual, logical, persistence and physical. This division provides a simple interface to abstract the users from low-level implementation details, such as programming languages and data storage employed, allowing them to focus in the concepts and processes to be modelled. The Fénix architecture is accompanied by a set of programming libraries to facilitate the access and manipulation of the structures created in this framework. We will also show how this architecture has been already successfully applied in different research projects.